Drug Development in Psychiatry 3031210530, 9783031210532

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Advances in Neurobiology 30

Matthew Macaluso Sheldon H. Preskorn Richard C. Shelton   Editors

Drug Development in Psychiatry

Advances in Neurobiology Volume 30

Series Editor Arne Schousboe Department of Drug Design & Pharmacology University of Copenhagen Copenhagen, Denmark

Advances in Neurobiology covers basic research in neurobiology and neurochemistry. It provides in-depth, book-length treatment of some of the most important topics in neuroscience including molecular and pharmacological aspects. The main audiences of the series are basic science researchers and graduate students as well as clinicians including neuroscientists (neurobiologists and neurochemists) and neurologists. Advances in Neurobiology is indexed in PubMed, Google Scholar, and the Thompson Reuters Book Citation Index. Editor-In-Chief Arne Schousboe University of Copenhagen Editorial Board Members Marta Antonelli, University of Buenos Aires, Argentina Michael Aschner, Albert Einstein College of Medicine, New York Philip Beart, University of Melbourne, Australia Stanislaw Jerzy Czuczwar, Medical University of Lublin, Poland Ralf Dringen, University of Bremen, Germany Mary C. McKenna, University of Maryland, Baltimore Arturo Ortega, National Polytechnic Institute, Mexico City, Mexico Vladimir Parpura, University of Alabama, Birmingham Caroline Rae, Neuroscience Research Australia, Sydney Ursula Sonnewald, Norwegian University of Science and Technology, Trondheim Alexei Verkhratsky, University of Manchester, UK H. Steve White, University of Washington, Seattle Albert Yu, Peking University, China David Aidong Yuan, Nathan S. Klein Institute for Psychiatric Research, Orangeburg

Matthew Macaluso Sheldon H. Preskorn  •  Richard C. Shelton Editors

Drug Development in Psychiatry

Editors Matthew Macaluso Department of Psychiatry and Behavioral Neurobiology University of Alabama at Birmingham Heersink School of Medicine Birmingham, AL, USA

Sheldon H. Preskorn Department of Psychiatry and Behavioral Science Kansas University School of Medicine-­ Wichita campus Wichita, KS, USA

Richard C. Shelton Department of Psychiatry and Behavioral Neurobiology University of Alabama at Birmingham Heersink School of Medicine Birmingham, AL, USA

ISSN 2190-5215     ISSN 2190-5223 (electronic) Advances in Neurobiology ISBN 978-3-031-21053-2    ISBN 978-3-031-21054-9 (eBook) https://doi.org/10.1007/978-3-031-21054-9 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

Contents

1

Drug Development in Psychiatry: The Long and Winding Road from Chance Discovery to Rational Development��������������������������������    1 Sheldon H. Preskorn

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The History of Drug Development in Psychiatry: A Lesson in Serendipity ������������������������������������������������������������������������������������������   19 Abhishek Wadhwa

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The Evolving Role of Animal Models in the Discovery and Development of Novel Treatments for Psychiatric Disorders������   37 Laura B. Teal, Shalonda M. Ingram, Michael Bubser, Elliott McClure, and Carrie K. Jones

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 Discovery and Development of Monoamine Transporter Ligands������  101 Shaili Aggarwal and Ole Valente Mortensen

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 Drug Development for New Psychiatric Drug Therapies��������������������  131 M. Lynn Crismon, Janet Walkow, and Roger W. Sommi

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Post-Approval Research in Drug Development: Priorities and Practices��������������������������������������������������������������������������������������������  169 David Williamson, Jack Sheehan, and Ella Daly

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 Discovery of New Transmitter Systems and Hence New Drug Targets������������������������������������������������������������������������������������������������������  181 Tiffany Schwasinger-Schmidt and Sheldon H. Preskorn

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 Reverse Engineering Drugs: Lorcaserin as an Example����������������������  195 Tiffany Schwasinger-Schmidt and Sheldon H. Preskorn

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 Back to the Future of Neuropsychopharmacology ������������������������������  207 Anton Bespalov, Marcel van Gaalen, and Thomas Steckler

10 Targeted  Treatments for Fragile X Syndrome��������������������������������������  225 Devon Johnson, Courtney Clark, and Randi Hagerman v

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Contents

11 The  Difficult Path to the Discovery of Novel Treatments in Psychiatric Disorders��������������������������������������������������������������������������  255 Valentin K. Gribkoff and Leonard K. Kaczmarek 12 Biomarkers  in Psychiatric Drug Development: From Precision Medicine to Novel Therapeutics ������������������������������������������������������������  287 Rudy Lozano Carreon, Ana Maria Rivas-Grajales, Nicholas Murphy, Sanjay J. Mathew, and Manish K. Jha 13 The  Role of fMRI in Drug Development: An Update ��������������������������  299 Owen Carmichael 14 Monoamine  Oxidase B (MAO-B): A Target for Rational Drug Development in Schizophrenia Using PET Imaging as an Example������������������������������������������������������������������������������������������  335 Kankana Nisha Aji, Jeffrey H. Meyer, Pablo M. Rusjan, and Romina Mizrahi 15 Genomics in Treatment Development����������������������������������������������������  363 Yogesh Dwivedi and Richard C. Shelton 16 Increased  Inflammation and Treatment of Depression: From Resistance to Reuse, Repurposing, and Redesign����������������������  387 Jennifer C. Felger 17 Experimental  Medicine Approaches in Early-Phase CNS Drug Development ��������������������������������������������������������������������������������������������  417 Brett A. English and Larry Ereshefsky Index������������������������������������������������������������������������������������������������������������������  457

About the Editors

Matthew Macaluso  is the Bee McWane Reid Professor and Vice Chair for Clinical Affairs in the Department of Psychiatry and Behavioral Neurobiology as well as the Clinical Director of the UAB Depression and Suicide Center. His research focus is on clinical psychopharmacology and its translation to clinical practice with a focus on treatment-resistant major depression. As clinical director, Dr. Macaluso oversees clinical trials of novel mechanism of action drugs, devices, and biologics to treat patients with severe forms of depression that are not responsive to currently marketed treatments. He is a highly experienced investigator in complex clinical trials and the translational neuroscience of mood disorders and has contributed most significantly in the area of novel treatment development. Dr. Macaluso completed medical school at the University of Medicine and Dentistry of New Jersey in Stratford, NJ, and graduated from the psychiatry residency program at the University of Kansas School of Medicine, where he was on faculty for 11 years before joining UAB in 2020. Sheldon H. Preskorn  is generally considered one of the world’s foremost experts in psychiatric drug development research having worked with over 145 pharmaceutical, biotechnology, devices, and diagnostic companies around the work and was a principal site investigator in all antidepressants and antipsychotics marketed in a 25-year period. His overarching goal has been throughout his career to bring science to the practice of psychiatry. His research focus is on clinical psychopharmacology and its translation to clinical practice with a focus on otherwise treatment-resistant psychiatric illnesses. In addition to being a consultant broadly to companies bringing products to the market, he has also worked with the FDA in many different capacities. Dr. Preskorn did his basic medical training at the University of Kansas School of Medicine where he also completed a two-year residency in anatomical pathology with a focus on neuropathology. He did his psychiatric residency at Washington

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About the Editors

University School of Medicine in St. Louis MO. During his residency, he did seminal work on the role of the locus coeruleus in the brain. He has continued related work throughout his more than 40-year career in academic medicine. Richard C. Shelton  is the Charles Byron Ireland Professor and Co-director of the UAB Depression and Suicide Center in the Department of Psychiatry and Behavioral Neurobiology in the Heersink School of Medicine at the University of Alabama at Birmingham. He is an internationally recognized researcher in the areas of translational neuroscience and clinical psychopharmacology of mood disorders. Dr. Shelton founded and co-directs the UAB Depression and Suicide Center with Dr. Yogesh Dwivedi. The Center has a clinic that provides advanced treatment options for depression including esketamine, electroconvulsive therapy, and vagal nerve stimulation, and it also conducts research ranging from basic molecular neuroscience and genomics to clinical applied research in mood disorders and suicide. Dr. Shelton is a translational neuroscientist, and his work spans from molecules to clinical trials. Recent work has included research on genomic predictors of depression and suicide and advanced therapies for depression. Dr. Shelton graduated from the University of Louisville School of Medicine and graduated from the psychiatry residency program at the Massachusetts Mental Health Center (now part of the Brigham and Women’s residency program) of Harvard Medical School in Boston. He then was a research fellow in the intramural program of the National Institute of Mental Health. He was a professor in the Department of Psychiatry at Vanderbilt University School of Medicine for 26 years before joining UAB in 2012.

Chapter 1

Drug Development in Psychiatry: The Long and Winding Road from Chance Discovery to Rational Development Sheldon H. Preskorn

Abstract Based extensively on tables and figures, this chapter reviews drug development in psychiatry with an emphasis on antidepressants from the 1950s to the present and then looks forward to the future. It begins with the chance discovery drugs and then moves to through their rational refinement using structure activity relationships to narrow the pharmacological actions of the drugs to those mediating their antidepressant effects and eliminating the effects on targets that mediate adverse effects. This approach yielded newer antidepressants which compared to older antidepressants are safer and better tolerated but nevertheless do still not treat the approximately 40% of patients with major depression (MD) which is unresponsive to biogenic amine mechanisms of action. This form of MD is commonly referred to as treatment resistant depression. Esketamine is an antidepressant which has a novel mechanism of action: blockade of the glutamate NMDA receptor. These studies coupled with earlier studies with other NMDA drugs suggest approximately 60% of patient with TRD are rapidly and robustly responsive to this mechanism of action. Thus, there appears to be three forms of MD based on pharmacological responsiveness: (a) 60% responsive to biogenic amine mechanisms of action, (b) 24% (i.e., 40 × 60%) responsive to NMDA but not to biogenic amine mechanisms of action, and (c) 16% (i.e., 40–24%) not responsive to either of these mechanisms of action. Scientific investigation of these three groups may yield important information about the pathophysiology and/or pathoetiology of these different forms of MD. This information coupled with studies into the neurobiology (e.g., imaging studies, connectomes to name a few approaches being used) and genetics of MD should provide the fundamental knowledge which will permit a rational search for and discovery of newer antidepressant drugs and other somatic and psychotherapeutic approaches to the treatment of patients with different forms of MD based on pathophysiology and S. H. Preskorn (*) Department of Psychiatry and Behavioral Science, Kansas University School of Medicine-Wichita Campus, Wichita, KS, USA e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 M. Macaluso et al. (eds.), Drug Development in Psychiatry, Advances in Neurobiology 30, https://doi.org/10.1007/978-3-031-21054-9_1

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pathoetiology. Examples are given of how such discovery and development have occurred in other areas of medicine and even in central nervous system (CNS) space including six novel mechanisms of action CNS drugs which have been successfully developed and marketed over the last 25 years. Keywords  Antidepressants · Central nervous system biogenic amines · Drug development · Esketamine · Major depression · Mechanism(s) of action · Psychiatric diagnosis · Relative receptor binding · Structure-activity relationships [For] knowledge of mental diseases one must have: (a) knowledge of the physical changes in the cerebral cortex, and (b) [knowledge of] the mental symptoms associated with them. Until this is known, we cannot hope to understand the relationship between symptoms of disease and the physical processes underlying them.—Emil Kraepelin [1], Father of modern psychiatry Symptoms and behaviors are the output of brain function whereas syndromes are man-­ made constructions.—Sheldon Preskorn [8]

This Chapter, which was adapted with permission from the Springer Nature book, Antidepressants: From Biogenic Amines to New Mechanisms of Action, will discuss the history of antidepressant drug development and put it into the broader context of psychiatric drug development. This chapter will focus on the history of and current status of antidepressant drug development but will also incorporate other concepts relevant to future antidepressants and other central nervous system (CNS) drug development. It will be heavily dependent on the writings of the author on these topics over the last 30  years. The chapter will be primarily focused on illustrative figures and tables with the minimum amount of text needed to explain the figures and tables, put them in context, and then transition to the next topic. All the articles in which figures and tables originally appeared are cited in the reference list. The reader who wants additional text and references on a given topic can do so by referring to the specific cited article of interest.

1.1 Current Status of Psychiatric Diagnosis as a Rate-­Limiting Step in Rational Psychiatric Drug Development In all of medicine, there are four levels of increasing sophistication of diagnosis as illustrated in Fig. 1.1 [12]. The first level is symptomatic diagnosis which is generally the presenting complaint of the patient to the treatment provider. For patients suffering from major depressive disorder (MDD), that presenting complaint may be feeling tired, absence of enjoyment, insomnia, or even headache to name but a few.

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Fig. 1.1 Diagnostic criteria pyramid – the four levels of increasing diagnostic sophistication. (Reproduced with permission from Preskorn and Baker [12]. © Preskorn, 2002)

In general, the psychiatrist is then taught to advance to a second level of diagnostic sophistication which is the syndromic level. The result may be that the patient presenting with these initial complaints may meet criteria for major depressive disorder or perhaps acquired immunodeficiency disorder (AIDS) if the patient also has Kaposi’s sarcoma, an opportunistic infection, and generalized wasting. To reach the third level of diagnostic sophistication illustrated in Fig. 1.1 requires testing for pathophysiological findings. In the case of AIDS, that would be a lowering of the CD 4 count or a positive Western blot test or a high HIV titer. In the case of MDD, there is no generally established testing, but some practitioners might test for cortisol nonsuppression or REM latency which have both been proposed as biochemical test for “endogenous major depression.” To reach the fourth level of diagnostic sophistication illustrated in Fig.  1.1 requires the establishment of a test for the etiological agent or a neurobiological condition which is not established for most psychiatric disorders with the possible exception being testing for the presence of autoantibodies against the NMDA receptor for patients suffering from NMDA receptor-mediated neuroencephalitis. In the case of AIDS, it would be to test for the presence of the etiological agent, the HIV virus. The above illustrates the basic problem with psychiatric drug development: The field is currently principally stuck at the syndromic diagnosis and has not been able – in general – to advance to the pathophysiological or to the even higher etiological level. However, that is not completely true. In the early 1900s, approximately 20% of admission to psychiatric hospitalization no longer exist. Those conditions were pellagra and general paresis of the insane. The former was due to vitamin D deficiency and the latter to tertiary syphilis. Once those etiological causes were identified and specific treatments identified, those conditions essentially no longer exist in the modern age and instead are consigned to being historical footnotes. In the future, the same will likely be true for major depressive disorder and other similar currently syndromic psychiatric diagnoses.

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1.2 What Possible Changes Lie Ahead for Psychiatric Diagnoses? Considering the philosophy expressed in my quote at the beginning of this paper, the National Institute of Mental Health (NIMH) in 2008 began to develop for research purposes new ways of classifying mental disorders based on behavioral dimensions and neurobiological measures. The goal being to move from the relatively primitive level of syndromic diagnoses to the next level pathophysiological diagnoses (Fig. 1.1). The author proposed a similar approach in a paper published 34 years earlier and illustrated in Fig. 1.2 [3]. The concept expressed in this figure is that there may be both syndromes which have an underlying biology and dimensional aspects of traits such as impulsivity, IQ, and introversion to extroversion which are independently, biologically, and environmentally determined which can modify the expression of the syndromic cluster such as agitated versus psychomotor retard MDD. Treatments addressing the pathophysiology or even better – perhaps – the pathoetiology of the syndromic diagnosis (MDD) and the pathophysiology of the modifying dimension (e.g., impulsivity) might be the ideal way to approach a given patient.

Fig. 1.2  Future of psychopharmacology. Interaction among syndromic diagnoses and between such diagnoses and dimensional aspects of personality. Space and the constraints of being a two-­ dimensional drawing of three-dimensional phenomena place limitations on this figure. In a three-­ dimensional figure, it would be clear that there is the potential for overlap between any two syndromic diagnoses and that the syndromic diagnoses are not on a personality trait continuum with respect to each other but rather that such traits are dimensionally present in all diagnoses and influence their expression. This figure also is not meant to imply that there are only three personality traits nor that the three depicted here are necessarily the most important (MDD major depressive disorders, ETOH alcoholism, SZ schizophrenia). (Reproduced with permission from Preskorn [3]. © Preskorn 1990)

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1.3 The History of Current Psychiatric Drug Development: Chance Discovery and Rationale Refinement The current treatment armamentarium for major depressive disorder (and psychotic disorders for that matter) owes their existence to two factors: first, chance discovery and then rationale refinement (Table  1.1) [4–6]. That is particularly true for the treatments aimed at the two of the most major syndromic diagnoses: affective and psychotic disorders. Chlorpromazine can be viewed as the “Adam” or “Eve” (whichever the reader prefers) to both the family of modern antipsychotics and modern antidepressants as illustrated in Fig. 1.3 [4–6]. In the interest of space and because the themes are the same, this text will not cover the antipsychotic line of the family of drugs while acknowledging that the first widely used class of antidepressants [i.e., tricyclic antidepressants (TCAs)] resulted from a failed medicinal chemistry attempts to develop better antipsychotics. The interested reader can review the primary papers cited in the reference list for details on the antipsychotic lineage if they wish. Briefly, chlorpromazine begat imipramine as a failed attempt by relatively blind medicinal chemistry to develop a better antipsychotic. The structural change leads to the loss of antipsychotic efficacy (i.e., no to weak D-2 receptor blockade) but the emergence of antidepressant efficacy (due to most likely the ability to inhibit the neuronal uptake of either norepinephrine or serotonin uptake). About the same time, there was a failed attempt to develop better antitubercular drugs based on the structure of isoniazid produced effective antidepressants. These drugs are called monoamine oxidase inhibitors (i.e., MAOIs) because they presumably work via their ability to inhibit monoamine oxidase, the rate-limiting enzyme in the degradation of three biogenic amine neurotransmitters: dopamine (DA), epinephrine (E), norepinephrine (NE), and serotonin (SE). The antidepressant activity of the MAOIs coupled with the antidepressant efficacy of the TCAs reinforced the Table 1.1  Early drugs that targeted the central nervous system Drug Amphetamine Cocaine Chlorpromazine Diazepam Imipramine Isocarboxazid Lithium Morphine Phenobarbital Reserpine

Class Stimulant Analgesic/stimulant Antipsychotic Anti-anxiety Antidepressant Antidepressant Mood stabilizer Analgesic Anticonvulsant Antipsychotic

Reproduced with permission from Preskorn [4]. © Preskorn 2010

Decade of discovery 1880s 1850s 1950s 1950s 1950s 1950s 1940s 2100 BC 1930s 1950s

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Fig. 1.3 Drug development based on chlorpromazine. (Reproduced with permission from Preskorn [5]. © Preskorn 2010)

idea that deficiency in either SE or NE neurotransmission was responsible for the depressive symptoms seen in patients with MDD. Armed with the knowledge of the antidepressant activity of TCAs and MAOIs in the 1970s coupled with the ability to use structure-activity relationships and in vitro methods to examine in vitro receptor binding lead to the development via medicinal chemistry of new compounds which were capable of blocking either SE or NE transporters either selectively or in a sequential manner to develop molecules (i.e., 10 times more potent at one than the other or both sequentially over less than a tenfold concentration range). The former were SE or NE selective reuptake inhibitors, whereas the latter were combined SE and NE reuptake inhibitors over their dosing range (i.e., generally capable of blocking SE reuptake at low concentrations and NE uptake inhibition at higher concentrations) (Fig. 1.4) [4–6]. In the case of bupropion, the goal was to develop a molecule capable of blocking NE and dopamine (DA) reuptake pumps, but the concept is otherwise the same. The “pharmacological refinement approach” allowed the development of drugs capable of affecting the desirable target (e.g., the SE transporter) at concentrations low enough to not engage from other targets which produce undesirable effects (e.g., acetylcholine muscarinic receptors). Importantly, this approach meant that the new drug did not have a novel mechanism of action different from the earlier antidepressants but instead had a more limited range of pharmacologic actions making it more focused and with a more limited adverse effect profile by eliminating effects on targets capable of mediating adverse effects which were off target. This strategy has led to the development of selective serotonin reuptake inhibitors (SSRIs) and serotonin-norepinephrine reuptake inhibitors (SNRIs) which are the latest, generally accepted antidepressants. The consequence of this iterative step without knowledge of the fundamental biology underlying the disorder has led to a plethora of drugs capable of treating patient suffering from a form of the illness which is responsive to their mechanism of action. Table 1.2 shows the relative receptor binding of most currently marketed antidepressants relative to the receptors currently known to be clinically relevant in terms of either producing antidepressant efficacy or “off-target” adverse effects [11].

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Fig. 1.4  Evolution of antidepressants. ACh acetylcholine, H histamine, α1 alpha adrenergic, NE norepinephrine, SE serotonin, DA dopamine, SNRI serotonin-norepinephrine reuptake inhibitor, SSRI selective serotonin reuptake inhibitor. (Reproduced with permission from Preskorn [4]. © Preskorn 1996)

All the drugs shown in Table 1.3 [9] are essentially a “rehash” or a realignment of the mechanisms previously suggested to play a role in producing an antidepressant response. The question is: Do they offer anything which is meaning- fully new in terms of additional efficacy? In general, the answer is no based on the results of the largest sequential trial of currently marketed antidepressants ever funded by the NIMH, the Sequenced Treatment Alternatives to Relieve Depression (STAR*D). That study showed that perhaps 40% of patients with MDD have a form of the illness which is not responsive to multiple trials of antidepressants which work via effects on biogenic amine antidepressants (i.e., SE, NE, or DA). That finding is the reason for the interest in antidepressants which work via non-­ biogenic amine antidepressants such as ketamine and related drugs.

1.4 The Future or Where to Go from Here? On the downside, one could look at the last 50 years of psychiatric drug development particularly regarding antidepressants and antipsychotics as an era in which the same mechanisms were rehashed repeatedly. That is simply because these mechanisms were known to work, and not enough was known about the biology of the illness to take many chances on speculative targets. Admittedly, some development work was tried on speculative targets but failed which is the reason why it is

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Table 1.2  Antidepressants’ relative receptor binding affinitya Branded hSET hNET hDAT 5-­HT1A 5-HT1B name Serotonin and norepinephrine reuptake inhibitors and antagonists at various neuroreceptors and ion channels Amitriptyline Elavil 4 34 >1000 Imipramine Tofranil 1 26 >5000 Nortriptyline Pamelor 4 1 261 Selective serotonin reuptake inhibitors Citalopram Celexa 1 >1000 >10,000 Escitalopram Lexapro 1 >1000 >10,000 Fluoxetine Prozac 1 545 >1000 Fluvoxamine Luvox 1 620 >1000 Paroxetine Paxil 1 450 >1000 Sertraline Zoloft 1 >1000 220 Selective norepinephrine reuptake inhibitors Desipramineb Norpramin 21 1 >1000 Reboxetine Vestra 8 1 >1000 Dual serotonin and norepinephrine (SE ≥ NE) reuptake inhibitors Desvenlafaxine Pristiq 1 27 >1000 Duloxetine Cymbalta 1 7.5 504 Levomilnacipran Fetzima 1 8 >1000 Milnacipran Savella 1 8 >1000 Venlafaxine Effexor 1 16 >10,000 5-HT2A antagonist and weak serotonin reuptake inhibitors Flibanserin Addyi 1 >1000 Nefazodone Serzone 9 18 17 Trazodone Oleptro 21 >1000 929 Specific histamine, serotonin, and norepinephrine receptor antagonist Mirtazapine Remeron >100,000 >10,000 >100,000 Dopamine and norepinephrine (weak) reuptake inhibitor Bupropion Wellbutrin 17 95 1 SSRIs + specific SE receptor activity Vilazodone Viibryd 1 >500 370 21 Vortioxetine Brintellix 1 71 >1000 9 33 Generic name

5-­ HT1D

5-HT2A

>1000 49 1 1

21

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Table 1.2 (continued) Generic name p5-HT2C 5-HT3 5-HT7 h alpha1 hM1 gpH1 D3 Serotonin and norepinephrine reuptake inhibitors and antagonists at various neuroreceptors and ion channels Amitriptyline – 25 16 1 Imipramine – 65 65 8 Nortriptyline – 148 34 1 Selective serotonin reuptake inhibitors Citalopram >1000 757 894 179 Escitalopram >1000 >1000 >1000 257 Fluoxetine 65 >1000 638 >1000 Fluvoxamine >1000 560 >5000 >5000 Paroxetine >10,000 >10,000 720 >100,000 Sertraline >10,000 >1000 >1000 >100,000 Selective norepinephrine reuptake inhibitors Desipramineb – 156 235 132 Reboxetine 875 >1000 933 44 Dual serotonin and norepinephrine (SE ≥ NE) reuptake inhibitors Desvenlafaxine >1000 >1000 >1000 >1000 Duloxetine >1000 >1000 >1000 >1000 Levomilnacipran Milnacipran 917 >1000 >1000 >1000 Venlafaxine >1000 >1000 >1000 >1000 5-HT2A antagonist and weak serotonin reuptake inhibitors Flibanserin >10,000 990 >100 Nefazodone – 1.2 522 1 Trazodone 1 5 >1000 45 Specific histamine, serotonin, and norepinephrine receptor antagonist Mirtazapine – >1000 >1000 1 Dopamine and norepinephrine (weak) reuptake inhibitor Bupropion – 10 95 10 SSRIs + specific SE receptor activity Vilazodone Vortioxetine 2 12 Reproduced with permission from Preskorn [10]. © Preskorn 2017

D4

>10,000

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Table 1.2 (continued) Key: h human, SET serotonin transporter, NET norepinephrine transporter, DAT dopamine transporter, p porcine, 5-HT serotonin, gp guinea pig, H histamine, M muscarinic, D dopamine, SE serotonin, NE norepinephrine, SSRIs selective serotonin reuptake inhibitors a Relative binding affinity (RRB) is the binding affinity of the drug for every receptor reported in the package insert in relationship to the drug’s highest affinity site. To calculate the relative binding affinity for each drug, its Ki for its highest affinity site is divided by itself, yielding 1, and next the Ki for the highest affinity site (which is the smallest concentration of drug needed to bind to any site) is divided into all its Ki’s for lower affinity sites (which is hence a higher concentration needed to bind to a lower affinity site); the result then is a number greater than 1. The larger that number, the higher the concentration needed to bind to the next potential target for the drug b This drug is also a selective norepinephrine reuptake inhibitor For each drug in this table, its highest affinity and its affinity expressed in nanomolar concentration are as follows: amitriptyline, H1 (1); bupropion, DAT (526); citalopram, SET (1.6); desipramine, NET (0.83); desvenlafaxine, SET (115); duloxetine, SET (1); flibanserin, 5-HT1A (1); fluoxetine, SET (1.1); fluvoxamine, SET (2.3); imipramine, SET (1.41); levomilnacipran, SET (11.2); milnacipran, SET (9); mirtazapine, Hr (0.14), nafazodone, H1 (6); nortriptyline, NET or H1 (4.35); paroxetine, SET (0.1); reboxetine, NET (7); sertraline, SET (0.3); trazodone, 5-HT2A (7.7); venlafaxine, SET (102); vilazodone, SET (0.1); vortloxetine, SET (1.6). Flibanserin and milnacipran are not labeled for antidepressant activity. They were initially developed and tested for this indication but clinical trials were not supportive. In the case of milnacipran, its active enationer, levomilnacipran, was successfully developed for an antidepressant indication2,14

not being discussed here. That is the reason why most of the psychiatric drugs approved from 2009 to 2016 (Table 1.3) had the same well-established mechanisms of action [9]. With that said, there have been six novel mechanisms of action drugs developed and approved over the last 25 years (Table 1.4) [7]. These drugs may point the way to the future because of common features in their development. First, they were directed at a single behavior of symptom rather than a syndrome or cluster of behaviors and symptoms which may have different mechanisms mediating them. Second, the circuitry underlying the disturbance was relatively simple and well established. Third, the outcome variable was relatively dichotomous (e.g., smoke, don’t smoke) rather than a reduction in a rating scale based on a compilation of the various disparate symptoms of a syndromic diagnosis such as MDD (e.g., the Hamilton Depression Rating Scale or the Montgomery-Asberg Depression Rating Scale). As knowledge of the biology underlying MDD continues to improve, it will guide the development of mechanistically new antidepressants. The other plus is that high-throughput screening can make new medications highly selective for their desired target. That is illustrated by the development done with tasimelteon and suvorexant which were screened against 200 targets which were not desired targets of the drug Table 1.5 [10]. The molecules, tasimelteon and suvorexant, were taken forward both because they affected their desired target at nanomolar concentrations and did not affect any of these other non-desired targets even at micromolar concentrations (i.e., 1000 times greater than the concentration needed to bind to their desired target).

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2010 21

2011 28

2012 39

2013 27

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1

Psychiatric and selected CNS drugs 3

Total drugs CNS Year approved drugs 2009 26 4 Labeled indication Mechanism of actiond Schizophrenia 5-HT2A > alpha-1 > D2 (1:2:17)

Vilazodone/Viibryd (Allergan)b Locaserin.Belviq [Arena Pharm (US distributor: Eisai)]c Vortioxetine/ Brintellix (Takeda)b

Lurasidone/Latuda (Sunovion)b Schizophrenia and depressed phase of bipolar I disorder Major depressive disorder Weight management/ obesity Major depressive disorder

NA

NA

5-HT 2C > 5-HT2A > 5-HT2B receptors (1:7:11) SET > multiple 5-HT receptors (1 ≤ 10)

NA

NA

NA

NA NA

Substrate for drug transporter Not P-gp; otherwise

SET > 5-HT1A (1:21)

5-HT2A ¼ 5-HT7 > D2 (1:1:2)

Schizophrenia and 5-HT2C > 5-HT2A > alpha-1 > D2 manic or mixed (1:3:4:7) episodes of bipolar I disorder SET > NET (1:8) Milnacipran/Savella Fibromyalgia (Allergan)c

Asenapine/Saphris (Allergan)b

Specific psychiatric or CNS drugs generic/brand name (manufacturer)a,b,c Iloperidone/Fanapt (Vanda)b

Table 1.3  Psychiatric and selected CNS drugs approved 2009–2016

(continued)

CYP2D6 > > CYP3A4/5, CYP2C19, CYP2C9, CYP2A6, CYP2C8, and CYP2B6

CYP3A4 > > 2C19 ¼ 2D6 Multiple CYP and non-CYP pathways

Mainly excreted unchanged with little to no drug metabolism CYP3A4

CYP1A2

Substrate for drug metabolizing enzymes CYP3A4 > CYP 2D6 ¼ carbonyl reductase

1  Drug Development in Psychiatry: The Long and Winding Road from Chance… 11

Labeled indication Major depressive disorder Onset and maintenance of sleep Tasimelteon/Hetlioz Non-24-h (Vanda)c sleep- wake disorder Bupropion plus Weight naltrexone/Contrave management in (Orexigen)a obesity

2015 45

4

4

NA

NA

NA

Mechanism of actiond SET > NET (1:8) Orexin 1 and 2 receptors

MT-1 and −2 receptors Bupropion: DAT > SET > NET (1:17:95); for naltrexone, see note belowe

Not a substrate for multiple transporters NA

NA

Substrate for drug transporter NA

Proaripiprazole/ Schizophrenia D2 > 5-HT1A > 5-HT2A (1:5:10) Aristada (Alkermes)a Cariprazine/Vraylar Schizophrenia and D3 > D2 ¼ 5-HT2B (1:6–8) (Allergan)b manic or mixed episodes of bipolar I disorder Flibanserin/Addy Hypoactive sexual 5-HT1A (Sprout)c desire in premenopausal females

Specific psychiatric Psychiatric or CNS drugs Total drugs CNS and selected generic/brand name Year approved drugs CNS drugs (manufacturer)a,b,c Levomilnacipran/ Fetzima (Allergan)b 2014 42 4 3 Suvorexant/ Belsomra (Merck)c

Table 1.3 (continued)

CYP3A4 > 2C19

CYP1A2, 3A4, and phenolic glucuronidation CYP2B6 (bupropion); non-CYP enzyme (naltrexone) Same as aripiprazole (i.e., CYP3A4 and 2D6) CYP3A4 > > 2D6

Substrate for drug metabolizing enzymes Mainly excreted unchanged CYP3A4

12 S. H. Preskorn

27

Total 254

16

1

Pimavanserin/ Nuplazid (Acadia)b

Schizophrenia and 5-HT1A > D2 > 5-HT2A > alpha; as an adjunct to 2C (1:3:4:5) antidepressants in major depressive disorder Psychosis in 5-HT2A > 5-HT2C (1:5) Parkinson disease Not a substrate for multiple transporters

NA

CYP3A4 and 3A5 > 2J2, 2D6, and various other CYP and FMO enzymes

CYP2D6 and 3A4

Reproduced with permission from Preskorn [10]. © Preskorn 2017 CNS indicates central nervous system, CYP cytochrome P-450 enzyme, D dopamine, DAT dopamine transporter, DOR δ-opioid receptor, FMO flavin- containing monooxygenase, gp guinea pig, H histamine, KOR κ-opioid receptor, M muscarinic, MOR μ-opioid receptor, MT melatonin, NA not available, NE norepinephrine, NET norepinephrine transporter, NME new molecular entity, P porcine, SET serotonin transporter, 5-HT serotonin Of these 16 drugs: a One was a combination of two existing drugs (bupropion+naltrexone); one was a prodrug of an existing molecule (proaripiprazole) b Nine were NMEs approved for a psychiatric indication c Five were NMEs approved for nonpsychiatric indications but which nevertheless targeted brain dysfunction (i.e., sleep, weight, or pain) with mechanisms of action that worked via the brain d Numbers in parentheses in the mechanism of action column represent the relative binding affinity of the drug for these respective targets, with 1 being the highest binding affinity for the drug and the larger numbers being how much the concentration of the drug has to increase to affect the next target (with the general rule in pharmacology being that a drug is selective for a target if its next binding requires more than a tenfold increase in concentration). For more details, see Preskorn et al.4 Most of the drugs listed in the table are full antagonists at their respective receptors. The few exceptions are aripiprazole, brexpiprazole, and cariprazine, which are partial agonists at the D2 receptor, and pimavanserin, which is an inverse agonist and antagonist at the 5-HT2A and 5-HT2C receptors (five times higher affinity for the 5-HT2A receptor than the 5-HT2C receptor) e Naltrexone and its active metabolite 6β-naltrexol are antagonists at the MOR, to a lesser extent at the KOR, and to a far lesser and possibly insignificant extent, at the DOR. The Ki affinity values of naltrexone at the MOR, KOR, and DOR have been reported as 0.0825, 0.509, and 8.02 nM, respectively, demonstrating a MOR/KOR binding ratio of 6.17 and a MOR/DOR binding ratio of 97.25,6

2

2016 26

Brexpiprazole/ Rexulti (Otsuka)b

1  Drug Development in Psychiatry: The Long and Winding Road from Chance… 13

Rozerem

Chantix

Belviq Belsomra

Ramelteon

Varenicline

Lorcaserin Suvorexant

6/27/2012 8/13/2014

5/10/2006

7/22/2005

6/27/2012 N/A

10/15/2014

3/1/2012

8/12/2014

Latest PI revision 9/18/2014

Reproduced with permission from Preskorn [7]. © Preskorn 2014 PI package insert a Difficulty with sleep onset b Marketed by Eisai c Difficulties with sleep onset and/or sleep maintenance

Arenab Merck

Pfizer

Takeda

Merck

Emend

Aprepitant

3/27/2003

Approval Originator date Glaxo 1/4/1991

Generic Brand name name Ondansetron Zofran

Weight loss Insomniac

Smoking cessation

Insomniaa

Indication(s) Chemotherapy-induced nausea and vomiting (CINV) CINV

Mechanism Serotonin 5-HT3 receptor antagonism Neurokinin (substance P)-1 receptor antagonism Melatonin (MT1, MT2) receptor agonism Acetylcholine nicotinic receptor alpha-4 beta-2 partial agonism 5-HT2c agonism Dual orexin 1 and 2 receptor antagonism

Table 1.4  Six central nervous system drugs with novel mechanisms of action developed in the past 25 years

No No

No

7/26/2013

7/24/2012

Generic available 7/2/2010

14 S. H. Preskorn

15

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Table 1.5  Receptors for which tasimelteon (10 μm) did not inhibit or stimulate binding by >50%a Adenosine A1 Adenosine A2A Adenosine A3 Adrenergic α1A Adrenergic α1B Adrenergic α1D Adrenergic α2 Adrenergic α2A Adrenergic α2C Adrenergic β1 Adrenergic β2

Dopamine D1 Dopamine D2L Dopamine D2S Dopamine D3 Dopamine D4.2 Dopamine D5 Endothelin ETA Endothelin ETB Epidermal growth factor Erythropoietin EPOR Estrogen Erα

Adrenergic β3

Estrogen Erβ

Adrenomedullin AM1

Aldosterone Anaphylatoxin C5a

G protein-coupled receptor GPR103 G protein-coupled receptor GPR8 GABAB GABAB1A

Androgen Angiotensin AT1 Angiotensin AT2

GABAB1B Gabapentin Galanin GAL1

Apelin (APJ)

Galanin GAL2

Atrial natriuretic factor

Glucocorticoid

Bombesin BB1 Bombesin BB2 Bombesin BB3 Bradykinin B1

Glutamate, AMPA Glutamate, Kainate Glutamate, NMDA Glycine, strychnine- sensitive Growth hormone secretagogue Histamine H1, central

Adrenomedullin AM2

Bradykinin B2 Calcitonin

Calcitonin gene- related Histamine H2 peptide CGRP1 Calcium channel L-type Histamine H3 Calcium channel N-type Histamine H4

Melanocortin MC1 Melanocortin MC3 Melanocortin MC4 Melanocortin MC5 Motilin Muscarinic M1 Muscarinic M2 Muscarinic M3 Muscarinic M4

Rolipram Ryanodine RyR3 Serotonin 5-HT1 Serotonin 5-HT1A Serotonin 5-HT1B Serotonin 5-HT2 Serotonin 5-HT2A Serotonin 5-HT2B Serotonin 5-HT2C

Muscarinic M5 N-formyl peptide receptor FPR1 N-formyl peptide receptor-like FPRL1 Neurokinin NK1

Serotonin 5-HT3 Serotonin 5-HT4 Serotonin 5-HT5A Serotonin 5-HT6

Neuromedin U NMU1 Sigma σ1 Neuromedin U NMU2 Sigma σ2 Neuropeptide Y, Y1 Sodium channel, site 2 Neuropeptide Y, Y2 Somatostatin sst1 Neurotensin NT1 Somatostatin sst2 Nicotinic Somatostatin sst3 acetylcholine Nicotinic Somatostatin sst4 acetylcholine α1 Nicotinic Somatostatin sst5 acetylcholine α7 Opiate δ (OP1, DOP) Tachykinin NK1 Opiate κ (OP2, KOP) Tachykinin NK2 Opiate μ (OP3, MOP) Tachykinin NK3 Orphanin ORL1 Thromboxane A2 Phorbol ester

Thyroid hormone

Platelet activating factor Platelet-derived growth factor Potassium channel [KA] Potassium channel [KATP]

Thyrotropin releasing hormone Transforming growth factor-β Transporter, adenosine Transporter, choline (continued)

S. H. Preskorn

16 Table 1.5 (continued) Cannabinoid CB1 Cannabinoid CB2 Chemokine CCR1 Chemokine CCR2B Chemokine CCR4 Chemokine CCR5 Chemokine CX3CR1 Chemokine CXCR2 (IL-8RB) Cholecystokinin CCK1 (CCKA) Cholecystokinin CCK2 (CCKB) Colchicine Corticotropin releasing factor CRF1

Hypocretin (orexin) receptor 1 Hypocretin (orexin) receptor 2 Imidazoline I2, central

Potassium channel [SKCA] Potassium channel HERG Progesterone

Inositol trisphosphate IP3 Insulin Interleukin IL-1 Interleukin IL-2 Interleukin IL-6

Progesterone PR-B

Leptin

Prostanoid, thromboxane A2 Purinergic P2X

Leukotriene (LTB4)

Prostanoid CRTH2 Prostanoid DP Prostanoid EP2 Prostanoid EP4

Leukotriene, cysteinyl Purinergic P2Y CysLT1 Leukotriene, cysteinyl Retinoid X receptor CysLT2 RXRα

Transporter, dopamine Transporter, GABA Transporter, monoamine Transporter, norepinephrine Transporter, serotonin Tumor necrosis factor Urotensin II Vanilloid Vascular endothelial growth factor Vasoactive intestinal peptide Vasoactive intestinal peptide 1 Vasopressin V1A Vasopressin V1B Vasopressin V2 Vitamin D3

Reprinted from Lavedan et al. [2] under a Creative Commons license Standard radioligand binding and enzyme inhibition assays were performed on receptors, binding sites, or enzyme systems obtained from various sources, including human, rat, mouse, guinea pig, rabbit, hamster, and bovine tissues (see Lavedan et al. [2], Supplemental Information), using the profiling screen and discovery screen panels (Panlabs) which consisted of 56 radioligand binding assays and 7 enzyme assays, respectively, and the SpectrumScreen panel (MDS Pharma Services) that included 170 pharmacological relevant targets (see Lavedan et  al. [2], Supplemental Information). In addition, the GABAA benzodiazepine and GABAB binding sites were also tested independently (Panlabs biochemical pharmacology assays). Tasimelteon was used at a concentration of 10 μm except for two enzyme assays (protein kinases C: PKCα and PKCβ) where it was used at 100 μm and for the melatonin receptors in the SpectrumScreen panel where four concentrations (10 nm, 0.1 μm, 1 μm, and 10 μm) were tested. A response was considered significant if there was ≤50% inhibition or stimulation for the assays The affinity of tasimelteon (10  μm) for the human hypocretin (orexin) receptor 1 expressed in transfected CHO cells and for the human hypocretin (orexin) receptor 2 expressed in transfected HEK-293 cells was determined in radioligand binding assays (Eurofins Cerep SA, Celle l’Evescault, France)

a

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17

1.5 The Immediate Future Which is Upbeat Between that development and the near future, ketamine and related drugs are the first legitimate hope for a new approach to treating patients with the form of MDD which is not responsive to biogenic amine antidepressants. While the antidepressant activity of ketamine and related drugs was initially discovered by chance as was the case with TCAs and MAOIs, it appears nevertheless to be robustly and rapidly effective in approximately 60% of patients whose depressive disorder is not responsive to biogenic amine antidepressants. This new era will not simply hold the promise for treating those patients but also provide biological insights into these different forms of the major depression: (a) those responsive to biogenic amine antidepressants, (b) those not responsive to biogenic amine antidepressants but to glutaminergic antidepressants such as esketamine, and (c) those not responsive to either of these forms of treatment. The ability to divide patients with the syndrome of major depression into these three categories has the potential to permit understanding the biological reasons for why they fall into those three groups. The knowledge gained from that and from the mechanisms underlying the response to esketamine will in turn lead to new developments just as was true the development of SSRIs and SNRIs from the knowledge gained from studies of TCAS and MAOIs. The figures and tables in this chapter come from the articles below. Each of these articles has its own reference list which the interested reader can access either through PubMed or on the Lippincott Williams & Wilkins website.

References 1. Kraepelin E.  In: Barclay RM, Robertson GM, editors. Dementia praecox and paraphrenia. Huntington NY: Krieger; 1915. 2. Lavedan C, Forsberg M, Gentile AJ.  Tasimelteon: a selective and unique receptor binding profile. Neuropharmacology. 2015;91:142–7. 3. Preskorn SH.  The future and psychopharmacology: potentials and needs. Psychiatr Ann. 1990;20(11):625–33. 4. Preskorn SH. CNS drug development. Part I: the early period of CNS drugs. J Psychiatr Pract. 2010a;16(5):334–9. 5. Preskorn SH.  CNS drug development: part II: advances from the 1960s to the 1990s. J Psychiatr Pract. 2010b;16(6):413–5. 6. Preskorn SH.  CNS drug development: part III: future directions. J Psychiatr Pract. 2011;17(1):49–52. 7. Preskorn SH. CNS drug development: lessons from the development of ondansetron, aprepitant, ramelteon, varenicline, lorcaserin, and suvorexant. Part I. J Psychiatr Pract. 2014;20(6):460–5. 8. Preskorn SH. CNS drug development: lessons learned part 2. Symptoms, not syndromes as targets consistent with the NIMH research domain approach. J Psychiatr Pract. 2015;21(1):60–6.

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9. Preskorn S. Psychiatric and central nervous system drugs developed over the last decade: what are the implications for the field? J Psychiatr Pract. 2017a;23(5):352–60. 10. Preskorn S.  CNS drug development, lessons learned, part 4: the role of brain circuitry and genes – tasimelteon as an example. J Psychiatr Pract. 2017b;23(6):425–30. 11. Preskorn S. Drug-drug interactions with an emphasis on psychiatric medications. West Islip: Professional Communications, Inc; 2018. 12. Preskorn SH, Baker B.  The overlap of DSM-IV syndromes: potential implications for the practice of polypsychopharmacology, psychiatric drug development and the human genome project. J Psychiatr Pract. 2002;8(3):170–7.

Chapter 2

The History of Drug Development in Psychiatry: A Lesson in Serendipity Abhishek Wadhwa Abstract  The goal of this book is to provide a guide on modern day drug development in psychiatry. However, in order to understand current practices in drug development, it is important to first understand the history of psychiatry including early attempts at drug discovery and develoment. The early history of psychiatry is mired with the use of inhumane experimental treatments and the institutionalization of patients in asylums. Some of the earliest drugs used in these asylums were meant to sedate patients rather than treat underlying mental disorders. The earliest identified drugs treating mental disorders were born out of serendipitous discoveries which later led to their clinical effects being demonstrated through clinical trials and case studies. This is evident from the history of chlorpromazine, monoamine oxidase inhibitors, tricyclic antidepressants, lithium, and others. We discuss in detail about each of these psychotropic drugs, the events leading up to their discovery, and their role in formulating the biological basis of mental disorders including schizophrenia, depression, and bipolar disorder. Psychiatry, it seems has worked its way backwards from first identifying treatments before understanding the biological basis of mental disorders, in a sharp contrast to the other fields of medicine. With our growing understanding of the etiopathogenesis of mental disorders, drug development in psychiatry is evolving to develop treatments that target the underlying physiology of mental disorders. Keywords  History · Psychopharmacology · Serendipity · Mental disorders · Catecholamine · Dopamine · Antipsychotic · Antidepressants · Drug development

2.1 Introduction Psychiatry has evolved over time in terms of how mental disorders are conceptualized and how biological treatments are used and developed. The focus of this book is on the development of biological treatments for mental disorders. In order to A. Wadhwa (*) University of Alabama at Birmingham, Department of Psychiatry and Behavioral Neurobiology, Birmingham, AL, USA e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 M. Macaluso et al. (eds.), Drug Development in Psychiatry, Advances in Neurobiology 30, https://doi.org/10.1007/978-3-031-21054-9_2

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A. Wadhwa

understand drug development in psychiatry, one must begin with an understanding of the historical underpinnings of the field. The term psychiatry (“Psychiatrie”) was first introduced by Johanne Christian Reil, professor of therapy at the University of Halle, in Germany in 1808. Reil, in his paper, argued that the cause of human disease is an essential interaction among the three domains of mental, chemical, and physical. The term “psychiatry” refers to a medical discipline rather than a philosophical or theological one [1]. Benjamin Rush is often considered the father of American psychiatry [2]. He is reported to have considered psychiatry as part of the field of medicine and devoted a large part of his teachings to the same. Building upon these concepts, Chiarugi, in Florence, for the first time suggested treating mental disorders using an approach which is respectful of patients and advocated for humane treatment. Jean-Baptiste Pussin and Philippe Pinel used this approach to institute “moral treatment” (1801), which was a psychological treatment and a sharp contrast to the violent treatments often used in asylums of the nineteenth century. Pinel further refined this approach into a “medical moral treatment.” This approach included reward-based activities, physical exercise, and offering nutritious food to patients while limiting the use of physical restraints. Pinel and Pussin reported a high success rate with “mortal treatment” and inspired American psychiatry to follow the same approach [3]. The concept of “medical moral treatment” inspired Dorothea Dix who became a leading figure of national and international movements to promote the safe and humane treatment of people with mental disorders. Dix played a vital role in establishing and expanding state funded facilities for the treatment of mental disorders. By 1860, 28 out of 33 states in the USA were reported to have at least one public psychiatric hospital [4, 5]. The second and third decades of the twentieth century saw major changes in the understanding of mental disorders by the general public and medical community. It was during this time that the somatic origins of mental disorders began being systematically evaluated [5]. This was also the time where prefrontal lobotomy was developed as a treatment. Prefrontal lobotomy was first introduced in the USA in 1937 and was widely used until the early 1950s before the release of chlorpromazine. Lobotomy was heavily criticized due to being invasive, inhumane, and permanently changing the personality of patients [6, 7]. Electroconvulsive therapy (ECT) was developed in 1938 by Cerletti and was extensively used in the US in its unmodified form. The use of ECT declined in the 1960s due to a number of factors including the introduction of antidepressant drugs as well as the negative and often inaccurate depiction of ECT in the media [8]. After World War II, psychoanalysis emerged with Freud’s theories gaining mainstream popularity [5]. Historically, there is documented use of psychotropics since long before the introduction of psychiatry into the practice of medicine. Ancient Greek and Indian civilizations documented the use of psychoactive substances to experience euphoria. The concept of using a drug for understanding mental disorders is reported to have been conceived by the French psychiatrist, Moreau De Tours (1845) [9]. Emil Kraeplin (1892) used the term “pharmacopsychology” to indicate the effects of drugs on psychological functioning. Kraeplin is reported to be among the first to promote the idea of treatment response to determine the clinical effect of a drug.

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21

Sigmund Freud is also regarded as an early figure in psychopharmacology as indicated in his famous letter to Maria Bonaparte, where he predicted that the way to understanding psychosis and would be guided by organic chemistry or access to it through endocrinology. These developments took place around the same time that a paper was published to describe the antipsychotic actions of Rauwolfia which had been utilized in Indian folk medicine for a very long time. This paper was published in an Indian medical journal and was largely overlooked by Western medicine [9]. The nineteenth century also saw the use of sedatives and hypnotics including drugs such as narcotics, chloral hydrate, and bromides, primarily to sedate and calm patients but not to treat specific mental disorders [10]. Moving into the twentieth century, the serendipitous discovery of several psychopharmacologic agents lead to the development of major classes of drugs to treat mental disorders. The focus of this chapter is on historical aspects of drug development, with a focus on serendipitous discovery. Other chapters in this book will focus on the use of structure activity relationships and animal models to further develop drugs for treating mental disorders. The book will also focus on modern approaches to drug development including reverse engineering, the role of neuroimaging, and the use of biomarkers including genetic and epigenetic markers in drug development research.

2.2 Chlorpromazine The serendipitous discovery of chlorpromazine was an early development for the budding field of psychopharmacology. Phenothiazines were developed in the late nineteenth century for use in the dye and textile industries. At the time, phenothiazines were recognized for their antiseptic and active parasitic properties and were further explored for their antihistaminic properties in the early twentieth century. In the 1930s and 1940s, there was interest in producing synthetic histamines for use in medical research. The pharmaceutical division of a French company, Rhône-­ Poulenc, in collaboration with research groups at the Pasteur Institute developed novel antihistamines based loosely on diphenhydramine. Paul Charpentier, a chemist at the company, modified and tested the antihistaminic properties of several phenothiazine compounds. One of his earlier successes was promethazine in 1947. Henri-Marie Laborit, a French surgeon, was experimenting with antihistamines for use in preventing surgical shock in the 1940s by creating a form of artificial hibernation by reducing hyperthermia. When Laborit administered promethazine to his patients he observed a unique psychological phenomena that he termed “euphoric quietude.” The cardinal features of “euphoric quietude” included (1) weak and reversible narcosis, (2) no clouding of consciousness, and (3) emotional indifference [10–12]. Simone Corvoiser, at Rhône-Poulenc, analyzed the sedative properties of the antihistaminic agents synthesized by Paul Charpentier and his team, identifying promethazine as a promising option. Charpentier continued to work on further

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alterations of the core nucleus of the molecule hoping to generate greater antihistaminic effects. Among the different derivatives, a compound created by introducing a chlorine atom into one of the rings of promethazine, R.P.4560, was sent for further testing in clinical settings. Laborit tested this new drug and noted that patients were more relaxed and calm before and after surgery when taking R.P.4560. He further predicted the possible application of these agents in treating psychiatric disorders [10–13]. A French psychiatrist, Pierre Deniker, is credited for introducing chlorpromazine into psychiatry. He is regarded as one of the pioneers of pharmacological treatments in psychiatry and an advocate for seeking out the biological basis of mental disorders. He conducted clinical trials at Sainte-Anne Hospital, in Paris, where he was the head of an inpatient psychiatric unit, along with Jean Delay. He reported a calming effect of chlorpromazine on agitated patients with psychosis and recognized the therapeutic potential of this new drug. Delay suggested chlorpromazine’s classification as a neuroleptic along with similar drugs producing effects of psychomotor retardation. The first controlled trial of chlorpromazine was conducted at the University of Birmingham (UK) by Joel and Charmain Elkes which was also notably the first recorded randomized, placebo controlled, trial in the history of psychiatry [10, 11, 14, 15]. Chlorpromazine was marketed under the trade name Thorazine by an American pharmaceutical company SKF who bought the North American rights to the drug and received US Food and Drug Administration (FDA) approval in May 1954. Despite its prominent use worldwide, the mechanism of action of chlorpromazine was largely unknown at the time. There was also very little evidence and consensus about the recommended dosage of the drug. In the early 1960s, it was thought that discrepancies in the earlier studies of chlorpromazine could have been due to the its hypothermic effects. Later studies on chlorpromazine controlled for the hypothermic effects of the drug and reported that it blocked dopamine receptors. This blockade induces a feedback mechanism increasing the metabolism of catecholamines. This was further substantiated by various studies demonstrating increased dopamine synthesis and metabolism induced by chlorpromazine. It was in the mid-1970s that the mechanism of action of chlorpromazine was clarified after it was established that chlorpromazine blocks dopamine receptors. These findings supported the dopamine hypothesis of schizophrenia [5, 10, 11, 16]. The dopamine hypothesis of schizophrenia emerged from the work of Carlsson and colleagues. They postulated that reserpine nonspecifically blocks the storage of all monoamines leading to their subsequent depletion by metabolic breakdown. He further established the involvement of catecholamines in the action of chlorpromazine and haloperidol. They demonstrated, using fluorometry, that antipsychotics including haloperidol and chlorpromazine cause an increase in noradrenaline and dopamine turnover in the brains of experimental rats leading to the conclusion that they might be acting by blocking dopamine receptors. In subsequent years, researchers established that antipsychotics increase the concentration of dopamine metabolites in the brain directly proportional to their potency. The dopamine hypothesis of

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23

schizophrenia has had a major influence on neurobiological research, specifically research into the mechanism of action of psychotropics [16].

2.3 Monoamine Oxidase Inhibitors The discovery of iproniazid and MAO inhibitors is another lesson in serendipitous discovery. Hydrazines originated in the 1870s during experiments carried out by the father of organic chemistry Emil Fischer. Hans Meyer and Josef Malley later synthesized isonicotinyl-hydrazine as part of their doctoral thesis in the 1910s. Development of this drug was largely dormant over the next 40  years until the 1950s. In the early 1950s, the antitubercular properties of hydrazines were discovered partly by chance. It is reported that large stocks of hydrazine were left over after World War II in the form of rocket fuel. These stocks were then distributed to chemical and pharmaceutical industries at a low cost which might have influenced the revival of interest in these compounds [10, 12, 15, 17]. The discovery of iproniazid’s antitubercular properties was mostly due to the efforts of two scientific teams working independently. These teams were led by Herbert Hyman Fox and Harry L Yale, respectively, for Hoffman La Roche laboratories and the Squibb Institute for Medical Research. In 1952, Irving J. Selikoff and Edward Robitzek published the results of their clinical study on the effectiveness of iproniazid and isoniazid in the treatment of tuberculosis. The studies were conducted at Seaview Hospital on Staten Island in New York. In addition to reporting the effectiveness of these drugs in tuberculosis, they found that iproniazid had effects on mood. The psychostimulant effects noted ranged from mood elevation to increase in social activity in patients who were being treated with iproniazid. To quote one of the observers “patients were dancing in the halls with holes in their lungs.” The positive effects on mood were initially thought to be secondary to improvement in respiratory function. These positive effects on mood were also observed in patients treated with iproniazid for other chronic illnesses such as rheumatoid arthritis or cancer [10, 17]. Mary Bernheim, a researcher at the University of Cambridge, describe an enzyme that she termed tyramine oxidase in 1928 which could bring about oxidative dissemination of biogenic amines. This enzyme was named monoamine oxidase in 1937 by a group led by Herman Blaschko. They demonstrated that this enzyme was capable of metabolizing adrenaline through oxidation. Quatel and Pugh identified this enzyme in the brain, although its significance was not clear at the time. In 1952, it was at Northwestern University in Chicago where Ernest Zeller observed for the first time that iproniazid inhibited MAO. Subsequent work on the enzyme showed that MAO converted serotonin to hydroxy indoleacetic acid. This was, for a long period of time, thought to be the only path for metabolism of serotonin. It was in 1957 at the National Institute of health (NIH), where Sydney Udenfriend and colleagues demonstrated a rapid increase in levels of serotonin in experimental animals after the administration of iproniazid. These findings led to further research on brain

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function and possible mechanism of action of antidepressants. It is in this context that the experimental studies of Charles Scott at Warner Lambert Research Laboratories were pivotal in the characterization of these drugs as antidepressants. He hypothesized that the tranquilizing effects of reserpine, an alkaloid of Rauwolfia Serpentina, were due to the release of serotonin. Inspired by Zeller’s work, he administered iproniazid to animals to limit the enzymatic destruction of serotonin to potentiate the tranquilizing effect of reserpine. However, pretreatment with iproniazid was observed to have a stimulating effect in animals. He termed this effect “marsilization” in reference to the trade name of iproniazid [15]. The clinical effects of iproniazid in non-tuberculosis depressed patients was first assessed by Nathan S. Kline and colleagues when they recruited 24 subjects (17 of which were diagnosed with schizophrenia and 7 with depression). This study was modeled after Scott’s experiments to demonstrate the stimulant effects of the drug in humans. The study was conducted at Rockland State Hospital in Orangeburg, New York. The patients were administered iproniazid 50 mg three times a day. The investigators reported substantial improvement in about 70% of the patients characterized by improved mood, decreased anhedonia, and improvement in social skills. These findings were reported at the annual meeting of the American Psychiatric Association in New York. Kline proposed the term “psychic energizer” while defining this drug’s action (Loomer et al. 1957). In spite of these positive results, Kline’s group ran into considerable difficulties conducting further studies when they lost the support of Hoffman Laroche as the company was doubtful about the marketability of the drug. Klein was able to eventually convince Hoffman Laroche to continue funding further development of iproniazid. Despite being marketed as an antitubercular agent, iproniazid continued to be prescribed to hundreds of thousands of patients affected by depression with good clinical response. The success of this drug is attributed in part to the good response observed in tuberculosis patients and partly due to lack of therapeutic alternatives to treat depression [12, 15, 17]. Iproniazid soon fell out of favor due to safety concerns including hypertensive crisis and liver toxicity. Other MAO inhibitors were developed with greater potency to inhibit MAO and relatively better side effect profiles. Often referred to as the classic MAOI’s, these constitute phenelzine, tranylcypromine, and isocarboxazid. Tranylcypromine differs from other MAOI’s in that it is structurally unrelated to hydrazines. Tranylcypromine is a cyclopropylamine, which was synthesized in 1948 as an analog of amphetamines. Its MAOI action was not discovered until 1959. Tranylcypromine was initially thought to have a more acceptable safety profile than other MAOI’s [10, 15]. The receptor isoforms of MAO were identified in 1968 by GP Johnston in rat brain. Further studies revealed that MAO-A, which is located preferentially in the intestinal lining, is responsible for deaminating adrenaline, noradrenaline, and serotonin. On the other hand, MAO-B isoforms are responsible for the metabolism of benzylamine and b-phenylethylamine. The classic MAOIs were shown to inhibit both isoforms. MAO-A was identified as the isoform responsible for the antidepressant action of MAOI’s. Moclobemide demonstrated reversible and selective inhibition of MAO-B. Selegiline is a newer selective inhibitor of MAO-B, which is mostly

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prescribed for the treatment of Parkinson’s disease and major depression. Transdermal selegiline has been shown to be effective in major depressive disorder. Currently, the three classic MAOIs and selegiline remain approved by FDA in the USA [15, 18].

2.4 Tricyclic Antidepressants The history of tricyclic antidepressants could be dated back to 1883 with the development of the first phenothiazine. The first TCA was synthesized by Professor Heinrich August Bernthsen in Germany while experimenting with chemical dyes, particularly methylene blue. Bernthsen created a phenothiazine that was used by J. Thiele and O. Holzinger to synthesize iminodibenzyl. Although, at the time it was not found useful by the textile industry, it was not until 1948 that in the pursuit of a novel sedative hypnotic, iminodibenzyl would be used as the basis for synthesizing 42 derivatives. These substances were then tested on laboratory animals and volunteers; one of these substances known as G-22150 was sent to a Swiss psychiatrist, Roland Kuhn, who dismissed its use as a hypnotic agent, given its unreliable results. He noted a “peculiar calming effect” of the drug. He further experimented to test the antipsychotic effects of the substance but ran into issues due to intolerance. In 1956, Kuhn received a compound termed as G-22355, a compound with lateral chains similar to chlorpromazine. Initial studies to test this compound in patients with schizophrenia did not improve psychotic symptoms. However, it was reported that some patients with schizophrenia developed hypomania while on the drug. Kuhn, in a letter to a pharmaceutical company in February 1956 pointed out possible antidepressant effects of the drug after observing clinical improvement in three of his patients diagnosed with depressive psychosis. Hence, the discovery of the antidepressant effects of TCAs was purely serendipitous [10, 14, 15, 19]. Kuhn further administered this drug to 37 depressed patients and presented the results at the World Congress of Psychiatry in Zurich in 1957. He reported that patients appeared more animated with improved communication and positive effects on mood. This drug was later named imipramine and his results were published in the journal “Schweizerische Medizinische Wochenschrift.” In addition to clinical effects, Kuhn described imipramine’s delayed onset of action and side effects including its anticholinergic effects. He observed that while a few patients experienced improvement in depressive symptoms 2–3 days after starting treatment, most experienced an improvement only after 1–4 weeks. He also described the suicide of a depressed patient with schizophrenia which he attributed to self-endangerment secondary to a decrease in inhibitions. This study was peculiar as Kuhn refrained from using structured rating scales and instead relied on direct observation of patients and nursing staff reports. This could be termed as a rudimentary form of a “trial” composed of case reports of patients who received the treatment. There was a lack of a control group and no standardized rating scales or statistical analysis were used. Despite all of its flaws, the study had a major impact on how

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psychiatrists treat depression and the subsequent development of antidepressants [12, 14, 15, 19]. This discovery however was met with skepticism in the medical community due to widespread psychodynamic/psychoanalytic theories of depression. It was the view of leading psychiatrists and psychologists of the time that drugs might help mask a few effects of depression but would not be as helpful in the long-term treatment of the illness. Despite this resistance to pharmacological treatment of depression, imipramine was introduced under the brand name Tofranil at the beginning of 1958. In September 1958, two studies were published in the American Journal of Psychiatry on the use of imipramine in patients with major depressive disorder. One of the studies was a reproduction of a lecture given by Roland Kuhn at Galesburg State Hospital. Kuhn’s reports were confirmed later in various studies. More than 60 studies were published worldwide by 1959 which reported the therapeutic effects and adverse reactions with imipramine. Imipramine was introduced in North America by Heinz E. Lehmann who had attended Kuhn’s lecture in Zurich and used the new drug to treat a group of Canadian patients. It was Lehmann’s study that demonstrated the positive clinical effects on a sample of 48 depressed patients that led to the introduction and marketing of imipramine in the USA. It was in 1959 that the first placebo-controlled clinical trial of imipramine was contacted by Ball and Kiloh who showed the efficacy of imipramine in what was then termed as endogenous depression and psychotic depression. Imipramine was approved by the FDA in 1959 for its use in major depressive disorder [10, 12, 14, 15, 17, 20]. Despite the success of imipramine, a second TCA would not come to the market until 1961. Amitriptyline was initially developed as an antipsychotic which was created after modifying the central ring of a thioxanthene. The manufacturer of amitriptyline, Merck, reached out to psychiatrists in 1958 to test for possible antipsychotic properties of the drug. Merck approached Frank J. Hyde, Jr. who was considered one of the leading biologist psychiatrists of the time from his studies on chlorpromazine. He used amitriptyline to treat 130 patients at the Baltimore Square hospital and reported on its antidepressant effects. Amitriptyline was subsequently approved by the FDA for its use in depression in 1961. The 1960s further saw the development of multiple TCAs, namely nortriptyline and desipramine, both of which were approved by the FDA in 1964. Other TCAs developed were protriptyline, doxepin, and clomipramine. The decade also witnessed the introduction of “tetra”-cyclic antidepressants, which were developed after modifying the dibenzazepine structure of imipramine. These drugs were termed as second-generation antidepressants and included maprotiline and mianserin [15, 21]. The discovery of imipramine also helped to define depression as a new disease entity. These developments were also occurring in parallel to the introduction of MAOIs. These developments helped bolster the idea of depression as a treatable illness. Similar to other psychopharmacological tools, the mechanism of action of TCAs was unclear at that time despite their popularity and clinical use. The development of these antidepressants was not only clinically relevant but was also a crucial factor for research into the etiology and pathogenesis of mood disorders. The introduction of spectrophotofluorimetry made it possible to detect changes in the

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level of monoamines and their metabolites in the brain and was critical in neuropsychopharmacology research [16]. It was with this technique that Bernard Brodie’s group at the National Institutes of Health (NIH) demonstrated the appearance of depressive symptoms with the depletion of brain levels of serotonin in experimental animals after they were administered reserpine [14, 17]. Reserpine, in the early 1950s was also being used for the treatment of schizophrenia, mostly in Germany. It was reported to precipitate depression and soon lost favor. Brodie’s team further demonstrated that pre-treatment with iproniazid was noted to nullify the effect of reserpine and there was no depletion of serotonin noted in these animals. Furthermore, if iproniazid was administered after reserpine there was no modification of its sedative effects. These observations gave rise to the hypothesis that alterations of mood could be defined by the amount of biogenic amines in the brain namely, serotonin and norepinephrine [10, 12, 15]. Although imipramine was shown to antagonize the effects of reserpine, the experiments did not yield useful findings on imipramine’s mechanism of action. Brodie’s team at NIH reported that imipramine inhibits the absorption of noradrenaline. Julius Axelrod led another NIH team which described that after TCA administration there was a reduction in uptake of noradrenaline at selective nerve endings. The later development of desipramine played a crucial role in understanding the modulation of norepinephrine as part of TCA’s mechanism of action [10, 15]. The work of Brodie and Axelrod would influence the biological understanding of affective disorders. The “catecholamine hypothesis” of affective disorders was described in two articles in 1965, one by J.J. Schildkraut in the American Journal of Psychiatry [22] and the other by William Bunney and John Davis in the Archives of General Psychiatry [23]. They hypothesized that depression might be associated with an absolute or relative deficiency of catecholamines. Their hypothesis was reliant on the effects of antidepressants as observed clinically and in vitro [10, 15]. The other prevalent hypothesis was the serotonergic hypothesis of depression. Betty Twarog, a researcher at Harvard, identified serotonin as a neurotransmitter [10, 15]. Alec J. Coppen demonstrated the improved therapeutic effects of MAOIs after the administration of tryptophan, a precursor of serotonin, in experimental animals [15, 16]. A Dutch psychiatrist Herman M. Van Praag reported the relationship between serotonergic dysfunction and the appearance of depression. Furthermore, a postmortem study of deaths by suicide by Shaw in 1967 demonstrated decreased brain concentrations of serotonin [17]. It was in 1968 that a Swedish group led by Arvid Carlsson demonstrated inhibition of reuptake of serotonin by TCAs. This would inspire Izyaslav P. Laplin and Gregory F. Oxenkrug to theorize the serotonergic basis for depression. The hypothesis stated that there was a deficit in serotonin level in certain brain areas which was responsible for the emergence of depression [15, 24]. The scientific and medical community towards the end of 1960s were in acceptance of the idea that the therapeutic effects of antidepressants, namely TCA and MAOIs, are mediated by increasing concentrations of serotonin and catecholamines. This would pave the way for the modern era of rational drug development and the

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introduction of medications that would target a specific set of neurotransmitters in the brain.

2.5 “Me Too” Drugs It is worth mentioning the phenomenon of “me too” drugs which entails the development of a drug that is chemically related to an existing drug with similar clinical outcomes and often a similar or identical mechanism of action. These new drugs rarely add in terms of therapeutic advantage but can potentially differ in terms of pharmacokinetics and side effect profiles. This phenomenon in part could be attributed to market competitiveness of pharmaceutical companies and can sometimes lead to useful treatments. The “me too” phenomenon is evident in the discovery of imipramine which was initially designed as an antipsychotic in parallel to chlorpromazine but was later found to have antidepressant effects. The development of various tricyclic antidepressants during the 1960s and 1970s could also be attributed to the “me too” phenomenon in a race by pharmaceutical companies to gain a competitive edge in the market. This “me too” phenomenon also extended to the SSRIs and other modern treatments. The “me too” phenomenon could be beneficial in cutting down costs or, in the case of SSRIs, offering alternative treatments [21].

2.6 Lithium Lithium is one of the simplest drugs in psychiatry. It is probably the earliest used psychotropic, although its definitive use treating psychiatric illnesses is attributed to serendipitous discovery. Lithium is a naturally occurring salt, hence its name comes from Greek word “lithos” meaning stone. The lightest metal in nature, lithium is distributed widely [25]. The earliest reports of using alkaline waters for the treatment of mania dates as far back as the fifth century. It was the work of two Swedish chemists, Johann August Arfwedson and Jons Jakob Berzelius, who isolated lithium from petalite and named the metal lithium. Lithium was marketed as an effective remedy for treating nervous disorders in the form of lithium water. Despite reports of lithium’s ill effects in patients with heart disease, it continued to be part of popular culture and was even once an ingredient in prominent sodas [12, 25]. Lithium was initially used as a medication for the treatment of gout through the works of Alfred Baring Garrod who was an internist working in London. Lithium was also widely used in the treatment of renal stones. Using lithium to treat psychiatric conditions was noted in 1870 by Cilas Weir Mitchell who was a neurologist in Philadelphia and used lithium bromide to treat “general nervousness” in his patients. One of the first instances of using lithium to treat mania was reported in 1971 by William Hammond at Bellevue Hospital in New  York. Since the drug used was

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lithium bromide, he was unable to ascertain which metal was responsible for the antimanic effects. Also, worth mentioning is the work of Carl G Lange who in 1886 introduced lithium in Denmark and promoted its use for the prevention of melancholic depression. These sporadic uses failed to gain traction partly due to the toxicity associated with lithium, which was used in larger doses at the time [12, 25, 26]. The introduction of lithium in the formal practice of psychiatry is attributed to the work of John Cade, an Australian psychiatrist, who observed mood symptoms in patients with thyroid disease. He recognized manic symptoms in patients with hyperthyroidism and depressive symptoms in patients with thyroid hypofunction. Given his observations, he hypothesized that mental illnesses could be caused by toxins generated due to hormonal imbalance that were being excreted in urine. He tested his hypothesis by injecting urine from patient with psychiatric illnesses and healthy controls into the peritoneal cavity of guinea pigs at different doses. He noted through his experiments that the urine from patients with mental illnesses was toxic at lower doses compared to healthy controls further cementing his belief that the urine of these patients contained toxic substances. He postulated urea as the toxic substance initially but soon through his experiments found the urine from manic patients continued to be more toxic even when controlled for urea and creatinine. He then concluded that there might be another substance in the urine of these patients that was potentiating the toxic effects of urea and focused on uric acid. To prove his hypothesis, he decided to inject laboratory animals with a solution of urea and varying concentrations of uric acid. Since these substances were poorly soluble in water, he decided to use lithium urate which is more soluble. He was surprised to find that lithium urate decreased urea toxicity. The convulsive effects observed earlier in guinea pigs injected with urine taken from manic patients were not observed after administering lithium urate. He then decided to experiment exclusively with lithium carbonate and observed the effect of reversible lethargy in the animals. These results encouraged him to study the effects of lithium in manic patients. Given concerns with the toxicity of lithium, he self-administered lithium carbonate to assess its safety. He later decided to administer lithium carbonate to patients suffering from schizophrenia and chronic mood disorders. The results of the study showed that lithium reduced excitement and agitation in patients with schizophrenia without altering the core symptoms of the illness. Lithium was not shown to be effective in chronic depression in the studies Cade conducted at the time. He also demonstrated the efficacy of lithium in the treatment of mania with the reappearance of manic symptoms after treatment discontinuation. These results were published in the Medical Journal of Australia in 1949 under the title “Lithium salts in the treatment of psychotic excitement” [27]. This discovery failed to gain much interest largely due to the cardiotoxic effects observed with lithium chloride. There was an absence of commercial interest from pharmaceutical industries given that lithium is widely available in nature. The early clinical trials with lithium were poorly designed and reported negative results further reinforced the notion (at the time) of its toxicity and limited utility in medicine [12, 20, 25, 26]. Although his work failed to garner much enthusiasm at the time, Cade’s original article inspired researchers to further test the use of lithium to treat mania. Most

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notable of which was the work of a Danish psychiatrist, Mogens Schou, who designed the first randomized controlled trial to assess the efficacy of lithium versus placebo published in 1954 [28]. He randomly assigned patients to active drug versus placebo with the flip of a coin. His results were published with reported symptomatic improvement in 40% of patients. The introduction of lithium in American psychiatry is attributed to Samuel Gershon who worked with John Cade before immigrating to the USA. He worked at the University of Michigan, and his work with lithium was pivotal in generating interest at Rowell laboratories for the commercial development of lithium. He published an article in 1960 encouraging use of lithium in Mania. Gershon eventually moved to New York where he became a well-­ known researcher studying lithium. Gershon worked on multiple trials of lithium which were designed to determine the clinical efficacy of lithium [29–31]. Ronald Fieve of the New York State Psychiatric Institute reported treating 19 patients with lithium who previously failed phenothiazine therapy. He reported that 11 of the 25 manic episodes experienced by these patients showed good response to lithium and the individual manic episodes were shorter compared to the duration of past episodes in these patients. The standard treatment of mania at the time was chlorpromazine and multiple studies confirmed the superiority of lithium when compared to chlorpromazine. The discovery of the Coleman photometer in 1958 also aided in the widespread use of lithium as it was now possible to measure the blood levels of lithium [12, 25, 26]. Several large clinical trials conducted at the Department of Veterans Affairs and the National Institutes of Mental Health (NIMH) in the later part of the 1960s demonstrated the efficacy and safety of lithium before it was formally approved by the FDA. Despite its proven effectiveness and widespread clinical use, obtaining FDA approval for lithium in bipolar disorder would prove to be an uphill battle. Despite lithium being widely recognized by government bodies around the world as a safe and effective treatment, it was not until 1970 that the US FDA formally approved lithium. At the time, the USA became the 50th country to officially approve lithium use in patients. In 1975 lithium was also approved by the FDA for the prophylactic treatment of mania [25, 26].

2.7 Valproate and Carbamazepine Valproic acid was synthesized by Beverly S.  Burton in 1881. It was used as an organic solvent given its good solubility in fat. It was a popular organic solvent used as a diluent for other drugs. George Carraz and colleagues working at Laboratoire Berthier in Grenoble, France in 1963 made an unexpected discovery while studying the anticonvulsant properties of Khellin compounds in experimental animals. As was the common practice of that time, valproic acid was used as a diluent to solubilize khellins. Study results demonstrated an anticonvulsant effect but failed to establish a dose response relationship. He further used the pentylenetetrazol convulsion model and

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incidentally realized that the diluent used in the solution possessed anticonvulsant activity instead of the khellin derivatives. They realized through this work that all of the solutions contain valproic acid and thus serendipitously discovered the anticonvulsant activity of valproate. After establishing the anticonvulsant properties, George Carraz and his group synthesized valpromide. Carraz further demonstrated that strychnine induced epileptic convulsions were prevented by valpromide but not by valproate [12, 25]. Following successful animal studies, Carraz collaborated with Sergio Borselli and Pierre Lambert in 1965 to conduct clinical trials in patients with epilepsy to test the efficacy and safety of valpromide and valproate. These trials were conducted at the psychiatric hospital of Brittany in France. The trials demonstrated that both valpromide and valproate have anticonvulsant effects and in addition some psychotropic effects were noted in patients. The psychotropic effects ranged from improvement in depression to mild euphoria. Lambert et al. in 1966 was the first to report valproate’s mood stabilizing effects in patients with bipolar disorder. Bowden et al. conducted a large multicenter, randomized, double blind, placebo controlled, and parent group trial which was supported by the Abbott pharmaceutical company. The recruited 179 acutely manic hospitalized patients who were randomly assigned to divalproex, lithium, or placebo. The investigators concluded that divalproex and lithium were significantly more effective than placebo in reducing the symptoms of acute mania. This study paved the way for FDA approval of divalproex sodium for its antimanic effects in 1995 [12, 25, 26]. Carbamazepine is a tricyclic anticonvulsant compound which was developed in the lab of J. R. Geigy in Basel, Switzerland. Its antiepileptic properties were demonstrated in 1963 by W. Theobad and H. A. Kunz. It was widely used in Japan in the 1960s as lithium was not available in the country at that time. One of the first series of trials of carbamazepine were conducted by Takezaki and Hanaoka for the treatment of bipolar patients. They published their results in 1971. Psychiatrists in Western countries were skeptical about the results because of a misconception of lower (cited as inadequate in Western literature) standards being used for the trials conducted in Japan (although the trial used similar research protocol to the trial that was used to demonstrate lithium’s efficacy). It received FDA approval in 1974 as an antiepileptic agent and would be approved in 2004 for treating mania [25].

2.8 Meprobamate and Mephenesin These sedative-hypnotics were developed by Frank Berger and William Bradley during their efforts to synthesize an antibacterial agent to target gram-negative bacteria that were resistant to penicillin. They believed that lengthening of a carbon chain of an existing disinfectant called phenoxetol could result in a drug with expected antibacterial effect. After the synthesis of this compound, they decided to assess its safety in experimental animals. To their surprise, they found that the mice injected with this drug developed a reversible flaccid paralysis of the voluntary

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skeletal muscles. They tested the compound, called mephenesin, in graduated doses to learn that it produces muscle relaxation and paralysis of all voluntary muscles while preserving consciousness. It was found to not affect the autonomic nervous system and resulted in spontaneous recovery. They used the term “tranquilization” to describe the effects of this drug in a report published in 1946 [10, 12]. Mephenesin is used clinically for producing muscle relaxation during light anesthesia. During use as an alternative to tubocurarine, the antianxiety effects of mephenesin were subsequently recognized. There were significant drawbacks limiting its use as an antianxiety agent: namely short duration of action, need for large doses due to low potency, and its major effect on the spinal cord [12]. Given these limitations there was a search for compounds with similar clinical properties while overcoming these shortcomings. Bernard Ludwig in 1951 introduced meprobamate, a compound similar to mephenesin. Berger in 1984 reported its selective action on the thalamus, hippocampus, and limbic system which were thought to be associated with anti-anxiety properties. Meprobamate was a widely used psychotropic which was eventually supplanted by benzodiazepines in the 1980s [10, 12].

2.9 LSD The psychedelic effects of LSD were accidentally discovered due to a lab accident. While trying to develop uterine stimulants and hemostatics, Albert Hoffman synthesized derivatives of ergot alkaloids in 1930s. This led to the synthesis of ergometrine which was then modified to form methergine, a compound with strong oxytocic and hemostatic properties. In subsequent efforts to develop an analeptic, Hoffman synthesized LSD-25. Analeptic refers to the phenomena of stimulation of respiration and reversal of CNS depression. The structure of LSD-25 was loosely based on nikethamide, a respiratory stimulant [12, 32]. It was while working in his lab that Hoffman accidentally absorbed LSD and felt its psychotropic effects. This experience led him to plan a self-experiment with this compound. After self-administration he reported: Last Friday, April 16, 1943, I was forced to stop my work in the laboratory in the middle of the afternoon and to go home, as I was seized by a peculiar restlessness associated with a sensation of mild dizziness. On arriving home, I lay down and sank into a kind of drunkenness which was not unpleasant and which was characterized by extreme activity of imagination. As I lay in a dazed condition with my eyes closed (I experienced daylight as disagreeably bright) there surged upon me an uninterrupted stream of fantastic images of extraordinary plasticity and vividness and accompanied by an intense, kaleidoscope-like play of colors. This condition gradually passed off after about two hours [32].

Sandoz quickly worked to develop the product which was then marketed under the trade name Delysid. This had two principal indications: analytical psychotherapies to induce states of relaxation and an experimental study of psychotic states [12].

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2.10 Conclusion and Future Directions Psychiatry has come a long way since its inception and subsequent designation as an integral yet specialized area of medicine. The practice of psychiatry has grown leaps and bounds and away from primitive and inhumane experimental treatments like low-sodium diets, forced vomiting, scalp bleeding, and blistering with the aim to reduce pressure in the brain by expelling fluids [5]. The father of American psychiatry, Benjamin Rush, was part of a few of these experiments [5, 33]. Due to a lack of available treatment options for the patients, individuals with mental disorders were frequently institutionalized. Most of the patients suffering from mental disorders were confined to asylums with little to no effort to help them be a functional part of the society [2, 4, 5]. The advent of psychopharmacology provided a much-needed boost not only in terms of the clinical treatment of psychiatric illnesses but also a pathway to understanding the pathophysiology of psychiatric illnesses. Much of our understanding of the biological basis of psychiatric illnesses is derived from the mechanism of action of these drugs that were discovered accidentally. Two of the major hypotheses of psychiatric illnesses, namely the catecholamine hypothesis of affective disorders and the dopamine hypothesis of schizophrenia, were both based on the effects of drugs used for the treatment of psychiatric illnesses. The field of psychiatry unlike other areas of medicine seemed to grow in reverse from treatment to understanding of etiopathogenesis. Our understanding of psychiatric illnesses has mostly been through studying the effects of drugs used for the treatment of these illnesses. For example, the development of selective serotonin reuptake inhibitors (SSRIs) was based on our understanding of the involvement of serotonin in major depressive disorder. As described in this chapter, most of the earliest psychotropics were discovered serendipitously. The earliest trials in psychiatry were poorly designed and mostly consisted of case series involving a small number of patients. Most of the studies lacked a control group and sometimes would only report positive outcomes. The four major drug discoveries including chlorpromazine, lithium, tricyclic antidepressants, and MAO inhibitors were all introduced in the practice of psychiatry through case series and lacked any control group. Eventually, the placebo-controlled trials of chlorpromazine, lithium, and imipramine did show favorable results. However, the antipsychotic properties of reserpine showed in earlier case series were not replicated in controlled trials. Also lacking in earlier studies of psychotropics was the use of standardized rating scales. The inclusion criteria were also broad owing to the narrative nature of DSM-I and II. There were also ethical concerns with the initial psychotropic trials as human studies were conducted before obtaining sufficient safety data and sometimes without appropriate informed consent. The introduction of randomized control trials was a shift towards an emphasis on results rather than the influence and expertise of individual clinicians. This meant that the results obtained from these trials could be replicated under standardized conditions. By the early 1970s, the FDA would judge a drug’s efficacy by the results of RCTs [20].

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The past few years have seen an advancement in our understanding of neurobiology due to the unprecedented growth and expansion of our understanding of neuroscience. It is now possible to develop drugs to target specific receptors in very specific areas of the brain. Modern drug development in psychiatry is discussed in the subsequent chapters of this book and seeks to achieve precision drug development through meticulously designed clinical trials focused on mechanism of action and targeting the underlying cause of the illness.

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17. Hillhouse TM, Porter JH.  A brief history of the development of antidepressant drugs: from monoamines to glutamate. Exp Clin Psychopharmacol. 2015;23(1):1–21. https://doi. org/10.1037/a0038550. 18. Chockalingam R, Gott BM, Conway CR. Tricyclic antidepressants and monoamine oxidase inhibitors: are they too old for a new look? Handb Exp Pharmacol. 2019;250:37–48. https:// doi.org/10.1007/164_2018_133. 19. Brown WA, Rosdolsky M.  The clinical discovery of imipramine. Am J Psychiatry. 2015;172(5):426–9. https://doi.org/10.1176/appi.ajp.2015.14101336. 20. Leon AC. Evolution of psychopharmacology trial design and analysis: six decades in the making. J Clin Psychiatry. 2011;72(03):331–40. https://doi.org/10.4088/JCP.10r06669. 21. Aronson JK, Green AR.  Me-too pharmaceutical products: history, definitions, examples, and relevance to drug shortages and essential medicines lists. Br J Clin Pharmacol. 2020;86(11):2114–22. https://doi.org/10.1111/bcp.14327. 22. Schildkraut JJ. The catecholamine hypothesis of affective disorders: a review of supporting evidence. Am J Psychiatry. 1965;122(5):509–22. https://doi.org/10.1176/ajp.122.5.509. 23. Bunney WE, Davis JM. Norepinephrine in depressive reactions. A review Arch Gen Psychiatry. 1965;13(6):483–94. https://doi.org/10.1001/archpsyc.1965.01730060001001. 24. Feighner JP.  Mechanism of action of antidepressant medications. J Clin Psychiatry. 1999;60(Suppl 4):4–11; discussion 12–3. 25. López-Muñoz F, Shen WW, D’Ocon P, Romero A, Álamo C. A history of the pharmacological treatment of bipolar disorder. Int J Mol Sci. 2018;19(7):2143. https://doi.org/10.3390/ ijms19072143. 26. Ruffalo ML. A brief history of lithium treatment in psychiatry. Prim Care Companion CNS Disord. 2017;19(5):27325. https://doi.org/10.4088/PCC.17br02140. 27. Cade JF.  Lithium salts in the treatment of psychotic excitement. 1949. Bull World Health Organ. 2000;78(4):518–20. 28. Schou M, Juel-Nielsen N, Stromgren E, Voldby H. The treatment of manic psychoses by the administration of lithium salts. J Neurol Neurosurg Psychiatry. 1954;17(4):250–60. https://doi. org/10.1136/jnnp.17.4.250. 29. Johnson G, Gershon S, Hekimian LJ. Controlled evaluation of lithium and chlorpromazine in the treatment of manic states: an interim report. Compr Psychiatry. 1968;9(6):563–73. https:// doi.org/10.1016/s0010-­440x(68)80053-­7. 30. Johnson G, Gershon S, Burdock EI, Floyd A, Hekimian L.  Comparative effects of lithium and chlorpromazine in the treatment of acute manic states. Br J Psychiatry J Ment Sci. 1971;119(550):267–76. https://doi.org/10.1192/bjp.119.550.267. 31. Shopsin B, Gershon S, Thompson H, Collins P.  Psychoactive drugs in mania. A controlled comparison of lithium carbonate, chlorpromazine, and haloperidol. Arch Gen Psychiatry. 1975;32(1):34–42. https://doi.org/10.1001/archpsyc.1975.01760190036004. 32. Hoffman. The Discovery of LSD.  Accessed April 4, 2022. https://catbull.com/alamut/ Bibliothek/HOFMANN%20Albert/discovery/lsd.htm. 33. Farr CB.  Benjamin rush and American psychiatry. 1944. Am J Psychiatry. 1994;151(6 Suppl):64–73. https://doi.org/10.1176/ajp.151.6.64.

Chapter 3

The Evolving Role of Animal Models in the Discovery and Development of Novel Treatments for Psychiatric Disorders Laura B. Teal, Shalonda M. Ingram, Michael Bubser, Elliott McClure, and Carrie K. Jones

Abstract Historically, animal models have been routinely used in the characterization of novel chemical entities (NCEs) for various psychiatric disorders. Animal models have been essential in the in vivo validation of novel drug targets, establishment of lead compound pharmacokinetic to pharmacodynamic relationships, optimization of lead compounds through preclinical candidate selection, and development of translational measures of target occupancy and functional target engagement. Yet, with decades of multiple NCE failures in Phase II and III efficacy trials for different psychiatric disorders, the utility and value of animal models in the drug discovery process have come under intense scrutiny along with the widespread withdrawal of the pharmaceutical industry from psychiatric drug discovery. More recently, the development and utilization of animal models for the discovery of psychiatric NCEs has undergone a dynamic evolution with the application of the Research Domain Criteria (RDoC) framework for better design of preclinical to clinical translational studies combined with innovative genetic, neural circuitry-­based, and automated testing technologies. In this chapter, the authors will discuss this evolving role of animal models for improving the different stages of the discovery and development in the identification of next generation treatments for psychiatric disorders. Keywords  Drug discovery · Animal models · RDoC · Psychiatry

Laura B. Teal, Shalonda M. Ingram and Carrie K. Jones contributed equally to this work. L. B. Teal · S. M. Ingram · M. Bubser · C. K. Jones (*) Department of Pharmacology, Vanderbilt University, Nashville, TN, USA Warren Center for Neuroscience Drug Discovery, Vanderbilt University, Nashville, TN, USA e-mail: [email protected] E. McClure College of Pharmacy and Health Sciences, Lipscomb University, Nashville, TN, USA © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 M. Macaluso et al. (eds.), Drug Development in Psychiatry, Advances in Neurobiology 30, https://doi.org/10.1007/978-3-031-21054-9_3

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3.1 Introduction The current prevalence of psychiatric disorders worldwide has increased over the last two decades [1]. Within the United States, over 20% of all adults experienced mental illness in 2020 [2]. While currently approved psychiatric drugs provide documented therapeutic benefits, successful treatment outcomes are often hampered by partial response rates and/or treatment resistance, dose-related adverse side effects, little to no efficacy for many symptom clusters, and decreased patient compliance with available dosing regimens [3–8]. Collectively, these findings underscore the tremendous unmet need to develop novel treatments for psychiatric disorders. Unfortunately, the discovery and development of novel chemical entities (NCEs) for psychiatric disorders has remained challenging with significantly lower rates of NCE progression from Phase II and Phase III efficacy trials to market launch relative to other therapeutic areas [9–11]. These industry-wide failures in the clinical development of psychiatric NCEs coupled with the limited understanding of the underlying pathophysiology for these disorders have resulted in the widespread withdrawal of pharmaceutical industry’s research and development (R&D) resources [9–11]. While all stages of psychiatric drug discovery and development have received extensive examination over the last two decades, as will be discussed in subsequent chapters, the limitations of animal models for the identification and characterization of psychiatric NCEs have come under particularly intense scrutiny. Criticisms have included the lack of sufficient in vivo target validation and strong disease model construct validity, the limited understanding of the pharmacokinetic to pharmacodynamic (PK/PD) relationships for the preclinical candidate (PCC) molecules, and the failure to establish optimized translational measures of target occupancy and/or functional target engagement critical for early proof-of-concept (POC) clinical studies [12–14]. To address these major concerns, researchers within both the academic and pharmaceutical industry communities are rapidly developing new strategies for the use of animals in the identification and validation of novel CNS drug targets and characterization of NCEs for psychiatric disorders. In this chapter, the authors will review the historical and current use of animals for modeling aspects of different psychiatric disorders. Next, we will discuss how these animal models are used to advance the progression of novel psychiatric NCEs through the stages of discovery. Finally, we will examine the ongoing application of the research domain criteria (RDoC) framework to improve preclinical to clinical translational studies coupled with novel genetic, neural circuitry-based, and automated testing technologies for novel psychiatric animal model development.

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3.2 Animal Models for Psychiatric Drug Discovery 3.2.1 Historical and Current Use of Animal Models for Psychiatric Disorders While multiple animal species are currently used in the different stages of drug discovery and development, including Caenorhabditis elegans [15, 16], Drosophila melanogaster [17], zebrafish [18, 19], dogs [20], and nonhuman primates [21], mice and rats continue to represent the predominant species for psychiatric drug discovery based on sufficient homology to humans and experimental feasibility [22]. Importantly, all research involving vertebrate animals requires institutional approval by an Institutional Animal Care and Use Committee (IACUC) at the organization where the research is conducted. The principles of the “three R’s” (3R’s) – replacement, reduction, and refinement – provide the critical guidelines for the ethical use of animals in academic and industry scientific research [20, 23]. These principles emphasize replacing animals when possible with in vitro assays, including immortalized or primary cell cultures; reducing the number of animals to be used with power calculation for determination of the appropriate sample size for each study; and refinement of testing procedures to minimize potential pain and stress in the test subjects. Although the ideal animal model for a given psychiatric disorder should replicate the complete phenotype of the human condition with its underlying etiology and/or pathophysiology, the development of such models has proven to be unrealistic due to the complex heterogeneous nature of the different psychiatric disorders and the presence of substantial comorbidities. Moreover, development of animal models for psychiatric disorders has been limited by the lack of understanding of the etiology and imbalances in the neural substrates underlying the pathophysiology of each disorder. As such, researchers have focused on animal models that represent one or more defined aspects of a particular disorder in a single preclinical species. This approach has allowed the examination of different alterations in the selected target mechanism(s) and/or associated biology, including changes in cellular signaling, neural circuity, and behavior under normal and pathological conditions. In some cases, animal models for psychiatric disorders have also been based on identification of different endophenotypes or quantifiable endpoints that are linked with psychiatric symptoms with shared underlying genetic influences [24]. As we will discuss below, the strength and suitability of a given animal model for a particular stage of the drug discovery process depend on its type and degree of validity.

3.2.2 Assessing the Validity of Animal Models The process of assessing the reliability of a particular animal model to accurately reflect a specific aspect(s) of a psychiatric disorder is based on three classic aspects of animal models, which were originally proposed by Willner in 1984 and are

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commonly known as construct, face, and predictive validity [25]. Construct (or etiologic) validity establishes a connection between the etiology and/or pathophysiology of the psychiatric disorder and the animal model. An animal model with high construct validity has strong mechanistic similarities to a particular psychiatric disorder etiology as demonstrated by homologous genetics and/or common disruptions in molecular and physiological signaling cascades. For example, a genetic mouse model based on a key disrupted gene, such as the chromosome 22q11.2 deletion in schizophrenia, may be considered to have high construct validity [12, 26]. However, it is also important to understand how closely the selected genetic variant being manipulated correlates with the specific psychiatric disorder. Since psychiatric disorders arise from complex interactions between multiple genetic and environmental factors, a single genetic change can often be associated with multiple psychiatric disorders. In the case of the chromosome 22q11.2 deletion, only 30% of individuals with this deletion meet the diagnostic criteria for schizophrenia or schizoaffective disorder [26, 27]. Thus, caution must be taken before declaring a single genetic deletion in mice a strong construct model of schizophrenia. Face validity refers to shared similarities between an observed feature or phenotype of the animal model and an anatomical, neurochemical, behavioral, or neuropathological aspect of the psychiatric disorders [25]. Often models with high face validity for psychiatric disorders share a common behavioral feature with the clinical presentation of a given DSM-5 disorder. For example, patients with schizophrenia exhibit deficits in sensorimotor gating, or an inability to properly filter out irrelevant sensory stimuli. This clinical symptom can be measured by studying changes in pre-pulse inhibition (PPI) of the acoustic startle reflex, wherein an auditory tone that provokes a startle response is measured with or without a preceding auditory tone, known as a pre-pulse, which does not provoke a startle response on its own. In healthy individuals, the presentation of a pre-pulse will markedly reduce the response to a subsequent startle stimulus. However, in individuals with schizophrenia, this pre-pulse-mediated inhibition of the acoustic startle response is attenuated [28, 29]. Comparable changes in PPI of the acoustic startle response can be assessed in both human patients with schizophrenia and in rodents; thus, a model which induces PPI deficits in rats, such as amphetamineinduced disruption of PPI, has high face validity [28, 29]. Predictive validity describes the correlation between the degree of efficacy of a particular pharmacologic mechanism in an animal model and the observed efficacy for one or more symptoms of a particular psychiatric disorder [25]. One example of an animal model with high predictive validity is the rodent forced swim test used to evaluate the antidepressant-like activity of novel treatments for major depressive disorder (MDD) [30, 31]. Mice or rats are placed in an inescapable transparent testing cylinder that is filled with water and their escape-related mobility behaviors are measured with the amount of time spent immobile, not actively swimming, considered a measure of learned helplessness [30, 31]. While this assay has low construct validity and only moderate face validity, it has high predictive validity since clinically efficacious antidepressant drugs reduce immobility duration [30, 31].

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As discussed below in the descriptions of representative animal models for the different psychiatric conditions, each model meets the different validity criteria to varying degrees making it important to use a variety of complementary animal models when evaluating the in vivo activity of a psychiatric NCE, to provide a broader efficacy profile that together approximates many aspects of the specific psychiatric disorder.

3.2.3 Types of Animal Models of Psychiatric Disorders In general, models for psychiatric disorders are categorized based on how the model is established, including genetic models, lesion models, pharmacological models, or behavioral models. When appropriate, these models can also be combined to form a multimodal model which may reflect more than one aspect of a given psychiatric disorder. Genetic models aim to understand the complex interaction between an individual’s genome and their environment [32, 33]. Genetic animal models can be used to validate a pharmacological target for drug development, to understand risk factors for developing a disorder, or to test potential treatments in a disease model. The design of animal models to study the connections between genetics, neurobiological mechanisms, and psychiatric illnesses also directly aligns with the RDoC framework [34, 35]. The traditional means of studying biological implications in psychiatric illnesses has been the constitutive or conditional modification of genes associated with psychiatric diseases; see the following review for more information about specific transgenic animal models for psychiatric disorders [36]. Constitutive gene expression studies in mice focus on the loss of function, gain of function, and the constitutive expression of chromosomal rearrangements indicated in psychiatric diseases [37]. Constitutive gene expression manipulations in psychiatric animal studies have been key in understanding biochemical changes that occur as a result of genetic variants and the lifelong effects, such as constitutive 5-HTT knockouts in understanding depression [38]. Constitutive gene modifications in animal are achieved by injecting the DNA of the gene of interest into the embryos of the animal model [39]. The resulting gene modifications are expressed throughout the entire animal and inherited in the offspring. Challenges to constitutive gene expression include the manipulation of genes resulting in lethal knockouts, adverse consequences in gene modifications in off-target organ systems, limited number of gene modifications in a single animal, and animal model validation. In general, constitutive expression is permanent and lacks control beyond initial expression of the genes. Conditional genetic expression studies in mice allow the modification of the gene based on a specific tissue or cell type and introduce inducible expression to control the onset of the genetic modifications in the animal model. Conditional models address the limitation of constitutive models in flexibility to control genetic modifications [37, 40–42]. The inducible characteristic of conditional gene

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expression systems is controlled by molecular switches. The tetracycline (Tet) system was one of the first established in transgenic animal models and successfully applied to neurogenomic studies in Huntington disease [43–46]. More recently, the Cre-LoxP system introduced a novel approach to tissue and site-specific modification of genes for better spatial and temporal expression of genes of interest in animal models [40, 42, 47, 48]. The advantage of the Cre-LoxP system is the ability to generate deletions, translocations, and inversions and alter gene copy number in any cell or tissue type [48]. Both approaches allow researchers to recapitulate genetic contributions of the illnesses as seen in humans with significant construct validity [12]. Furthermore, the use of these approaches has allowed researchers to identify endophenotypes that translate to human studies and the impact of genetic mutations on neurocircuitry abnormalities in models where polymorphisms are prevalent [35, 49]. However, conditional and constitutive genetic animal models are limited to single gene modifications in an animal and embryonic engineering. These limitations largely affect study designs to address multiple genetic variants that contribute to psychiatric illness comorbidities. Another common method of generating an animal model is a pharmacological challenge. In a pharmacological model, a drug with a known mechanism is administered to an animal, and the resulting behavioral or physiological changes are examined. For example, the psychostimulant amphetamine is often used as a pharmacological challenge to mimic underlying hyperactivity of the mesolimbic dopaminergic circuit correlated with similar circuitry changes and the positive symptoms in schizophrenia. A single dose of amphetamine robustly induces hyperactivity, and repeated dosing can exaggerate this hyperactivity accompanied by increased dopamine efflux from the nucleus accumbens and dorsal striatum [50]. In addition to hyperactivity, amphetamine also produces deficits in PPI of the acoustic startle reflex comparable to those observed in patients with schizophrenia (described in more detail under section “Schizophrenia Spectrum and Other Psychotic Disorders”) [51]. In both cases, amphetamine is used as a pharmacologic agent which induces behavioral changes that model circuit changes and/or symptoms of schizophrenia in rodents. A third method of animal model generation is the lesion model. Lesion models are used when ablation of a specific brain region can mimic symptoms of a CNS disorder. For example, in Parkinson’s disease, dopamine neurons within the substantia nigra deteriorate. In rodents, this can be modeled using 6-hydroxydopamine (6-OHDA), which selectively causes cell death in dopaminergic neurons. 6-OHDA lesions of the substantia nigra are therefore used to model a variety of symptoms of Parkinson’s disease [52]. This model, however, differs from the progression of Parkinson’s disease because the effects of the lesion develop rapidly over weeks versus mimicking the slow neuronal death in the human disorder over years. Despite this, the lesion model recreates the major neurological change seen in late-stage Parkinson’s disease, making it a good model for testing potential drug treatments targeting that patient population. Behavioral models assess a specific behavior in a certain context, often combined with another model or drug treatment. For example, a common behavioral model

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used in the assessment of antidepressant-like activity is the FST (defined in Sect. 3.2.2) [31]. FST is often used to assess differences in antidepressant-like activity associated with neurochemical lesion, genetic, and/or pharmacologic challenges. In addition, as will be discussed under the specific psychiatric disorder sections listed below, several stress-related behavioral models, such as chronic unpredictable mild stress and chronic social stress, are used to model different aspects of complex psychiatric disorders of depression, anxiety, and PTSD including anxiogenic-like and/or depressive-like activity. In the following sections, we will discuss some of the classical models for multiple psychiatric disorders. Each section is accompanied by a table with the following information: (1) preclinical rodent models, (2) biological rationale/ disorder etiology, (3) chronic neurobiological changes for chronic models or acute effects of pharmacologic treatment for the acute challenge models, (4) model validity, (5) utilization in stages of drug discovery, (6) FDA-approved drugs with demonstrated preclinical efficacy. Major Depressive Disorder Numerous genetic animal models for MDD have been designed using transgenic mice expressing different genetic variants of the following targets, including serotonin, norepinephrine, N-methyl-D-aspartate (NDMA) receptor, corticotropin-­ releasing hormone receptor-1, and BDNF, all of which have been hypothesized to contribute to the etiology of MDD [53]. More recently these genetic model approaches are being combined with optogenetic technologies to directly test the contributions of key disrupted brain circuits relevant to MDD [54, 55], as will be described in more detail in Sect. 3.4.2. There are two important acute models for MDD with high predictive validity that are used routinely from early-through late-­ stage lead optimization, specifically the forced swim [56], and tail suspension tests [57–59]. Both assays model a state of learned helplessness and are highly sensitive to the anti-depressant effects of all major approved classes of antidepressants [60] (see Table 3.1). In addition, there are a number of interesting chronic stress models with increased construct validity for modeling induction of chronic stress and anhedonic-­like behavioral states, including the unpredictable chronic mild stress [61, 62] and chronic social stress models [63, 64] (see Table 3.1). In the case of the unpredictable chronic mild stress model, mice or rats are presented daily with a series of unpredictable mild stressors in a schedule that prevents habituation, including changes in housing materials, light cycles, exposure to novel odor cues, food or water restrictions, none of which induce harm to the test animal [65]. In the case of the chronic social stress model [64] (also known as the resident/intruder social defeat test) resident mice undergo daily exposure to a larger, more aggressive intruder mouse in their home cage to establish dominance (see Table  3.1). Over the course of a 3–4 day period, rodents undergoing either the unpredictable chronic mild stress model or the chronic social stress model display significant behavioral and neurochemical changes associated with the development of

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anhedonic-like behaviors. These include increased immobility in the FST [66–68] and decreased sucrose preference [66, 68, 69], social interaction [70], locomotor activity [68, 71], food intake [71], and intracranial self-stimulation (ICSS) [69, 72] (see Table 3.1) along with significant alterations in c-Fos expression in key brain regions that modulate stress effects including the prefrontal cortex (PFC), hippocampus, and amygdala [73], disruptions in the normal hypothalamic-pituitaryadrenal axis functions [62, 66, 74], changes in mesolimbic reward circuitry signaling [75], and decreased dendritic spine density in the PFC and hippocampus [76] (see Table 3.1). ICSS is an interesting model with high construct validity and moderate face validity for assessing the anhedonic-like behaviors and responses of the brain reward circuitry [77]. ICSS involves implanting an electrode within the ventral tegmental area (VTA) or lateral hypothalamus, which the animal can activate by lever pressing to obtain direct brain stimulation at these rewarding areas. Animals with an anhedonia-like phenotype will exhibit increased ICSS thresholds, manifesting in decreased ICSS responding, thereby assessing the anhedonic-like behaviors and responses directly in the reward circuitry of the brain [77]. Overall the majority of depressive-like, anxiogenic and anhedonic-like activity in animals exposed to either unpredictable chronic mild stress and chronic social stress can be reversed with chronic exposure to the majority of clinically approved antidepressants [38, 78–91]. For more information on animal models for MDD, see the following reviews [53, 65, 92]. The Food and Drug Administration (FDA) approved therapies for MDD include selective serotonin reuptake inhibitors (SSRIs) such as citalopram and fluoxetine, serotonin/norepinephrine reuptake inhibitors (SNRIs) such as venlafaxine and duloxetine, tricyclic antidepressants such as imipramine and desipramine, the atypical antidepressant reboxetine, the monoamine oxidase inhibitor (MAOI) selegiline, the γ-aminobutyric acid subtype A (GABA-A) receptor positive modulator brenaloxone, and the NMDA receptor  antagonist esketamine. Deep brain stimulation has been studied in antidepressant-resistant rodents following chronic social stress and chronic mild stress and also demonstrates normalization of depressant behaviors [80–83]. While SSRIs remain a first line of treatment for MDD, this class of medication is also has associated dose-limiting side effects that include increased suicide risk (a side effect common to all antidepressants), serotonin syndrome, and sexual dysfunction [93]. Unfortunately, only 30% of patients receiving treatment for MDD symptoms experience full remission, and 50% have no response to treatment [94]. More recently, the FDA approval of esketamine marks an exciting approval of a novel treatment for treatment-resistant depression [95]. However, its use is strictly controlled because of potential abuse liability and sedating effects [96]. Generalized Anxiety Disorder Behavioral models for GAD in rodents consist of freezing or hypoactivity, vigilance, and defensive behaviors, and decreased food intake [97]. Chronic social stress, chronic mild stress, and single prolonged stress models are all used to induce

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Table 3.1  Animal models for major depressive disorders Models to induce depression-like symptoms Model Chronic Preclinical Biological neurobiological validity rodent model rationale/ changes disorder etiology

FDA-approved drugs with demonstrated preclinical efficacy SSRI: citalopram, Lead Face: Cortisone ↑ Unpredictable Repeated moderate optimization fluoxetine, chronic mild unpredictable [277], HDAC-5 in PFC Construct: Preclinical paroxetine exposure to stress TCA: mild stressors ↓ [84], dopamine moderate candidate imipramine, Predictive: selection cell firing in that are not desipramine moderate VTA ↓↑ [75], harmful, to NE/DA reuptake synaptic changes induce inhibitor: anhedonic-like in lateral reboxetine behaviors [61, amygdala [85], NMDA amygdala, 65, 78, 276, antagonist: hypothalamus, 277] esketamine and brainstem c-Fos changes [73] PFC-amygdala Chronic Repeated SSRI: citalopram, Lead Face: circuit [64], social stress exposure to moderate optimization fluoxetine, social stressors Na+/K+ ATPase Construct: Preclinical paroxetine activity in that are not TCA: moderate candidate amygdala ↓ harmful, to imipramine, Predictive: selection [278], NAc-VTA moderate induce desipramine anhedonic-like circuit activity ↑ NE/DA reuptake behaviors [63, [279] inhibitor: 65, 78, 276] reboxetine SSRI: citalopram, Social Isolation as a Face: low Disease NAc-VTA fluoxetine, isolation stressor to circuit activity ↑ Construct: etiology paroxetine induce anxiety [279], synaptic moderate Lead or depression-­ spine density in Predictive: optimization TCA: imipramine Preclinical desipramine, low like behaviors PFC ↓ [76], NE/DA reuptake candidate ACTH ↓ [74], [65, 86, 280, inhibitor: selection Hippocampal 281] reboxetine BDNF and 5-HT metabolism ↓ [282] TCA: Face: low Disease Sensitized Learned Inescapable desipramine Construct: etiology hippocampal helplessness stressor such SSRI: fluoxetine, moderate Lead norepinephrine as foot shock Predictive: optimization sertraline release [283], to induce high BDNF and behavioral HDAC-5 despair and expression in helplessness hippocampus ↓ [65, 87, 276] [284] Utilization in drug discovery

(continued)

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Table 3.1 (continued) Pharmacodynamic models to assess antidepressant-like activity of test compounds Utilization FDA-approved Preclinical Biological Antidepressant-­ Model drugs with in drug rodent model readout induced neural validity demonstrated discovery circuitry preclinical changes efficacy SSRI: citalopram, c-Fos regulation Face: low Early Forced swim Latency to fluoxetine, and in the amygdala Construct: hit-to-lead test and/or total paroxetine Lead low immobilization [91], Acute ↑ Predictive: optimization SNRI: activity in DA time as a venlafaxine and high SNc, chronic ↑ measure of duloxetine activity in DA learned TCA: imipramine helplessness or VTA [285] and desipramine Spine density in behavioral NE/DA reuptake PFC ↓, GluR1 in despair [56, inhibitor: 65, 78, 88–90] PFC ↓ of male reboxetine rats, NMDA receptor synapsin-1 in antagonist: PFC ↓ [76] esketamine GABAA PAM: allopregnanolonea SSRI: citalopram, Face: low Early Amygdala, Tail Latency to Construct: hit-to-lead hypothalamus, suspension and/or total fluoxetine, Lead low immobilization and brainstem paroxetine Predictive: optimization TCA: c-Fos changes time as a high [58] measure of imipramine, learned desipramine, helplessness or NE/DA reuptake behavioral inhibitor: despair [57, reboxetine 65, 78, 276] SSRI: citalopram, Face: low Lead Sucrose Consumption ↑ PFC and Construct: optimization fluoxetine, and preference hippocampus of sucrose-­ paroxetine low mTOR, ERK water versus TCA: imipramine plain water as and p70S6K [61] Predictive: and desipramine HDAC-5 in PFC low a measure of NE/DA reuptake ↓, synaptic pleasure inhibitor: changes in seeking reboxetine behaviors [61, lateral amygdala NMDA receptor [85] 65, 86, 280] antagonist: esketamine (continued)

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Table 3.1 (continued) Intracranial self-­ simulation

Lever pressing NE in BNST ↑ [72, 288] to stimulate VTA dopamine neurons, which is rewarding [77] decreased ICSS is anhedonia-like [60, 69, 96, 286, 287]

Face: moderate Construct: moderate Predictive: high

Lead optimization Preclinical candidate selection

SSRI: escitalopram (acute only), fluoxetine NE/DA reuptake inhibitor: bupropion BZDs: diazepam

Abbreviations: ACTH adrenocorticotropic hormone, ATPase adenosine triphosphatase, BDNF brain-derived neurotrophic factor, BDZ benzodiazepine, BNST bed nucleus of the stria terminalis, DA dopamine, ERK extracellular signal-regulated kinase, HDAC-5 histone deacetylase 5, mTOR mammalian target of rapamycin, NAc nucleus accumbens, NE norepinephrine, NE/DA norepinephrine/dopamine, NMDA N-methyl-D-aspartate, PFC prefrontal cortex, SNc substantia nigra pars compacta, SNRI serotonin/norepinephrine inhibitor, SSRI selective serotonin reuptake inhibitor, TCA tricyclic antidepressant, VTA ventral tegmental area, 5-HT serotonin a Allopregnanolone, a steroid hormone, was examined in preclinical assays. The FDA approved drug is brenaloxone, an IV formulation of allopregnanolone

anxiogenic-like behavior in rodents [98]. Behavioral tests used to assess anxiogenic-­ like behaviors acutely or after exposure to stressors, include, but are not limited to, elevated plus maze, light/dark box test, locomotor and exploratory activity, marble burying, and punished responding. The elevated plus maze (EPM) consists of two dark (enclosed) arms and two light (open) arms arranged as a plus-shape that is raised above the floor of the testing room [99]. Time spent in the open domains is interpreted as increased anxiolytic-­ like activity because these areas are more exposed to natural predation and heights. The light/dark box test uses an arena with a dark chamber and a light chamber. Longer times spent in the lighter chamber indicates increased anxiolytic-like activity, while more time spent in the darker chamber indicates increased anxiety-like behavior, similar to the EPM [100]. Marble burying in rodent models has been established as an anxiogenic-like behavior [101]. Burying is a natural response by rodents when experiencing stress that is also observed when presented with a marble in their bedding [102]. Punished responding, also known as the Geller-Seifter operant test for detection of anxiolytic-like drug effects, shows particular efficacy with benzodiazepines such as diazepam [103]. Rodents are initially conditioned to press a lever for either a food pellet or liquid reward. During the second phase of the testing, a discrete foot shock is delivered after a fixed number of lever presses for rewards which suppresses further lever pressing behavior to avoid additional shocks. However, lever pressing for reward can be restored with benzodiazepine treatments [104]. The neurobiological changes in GAD preclinical models largely involve changes in plasma levels of corticosterone and glucocorticoid receptor expression in the PFC. There are also reports of sex differences in corticosterone levels and how these differences lead to differences in anxiety-like behavior [105, 106]. Additional changes in c-Fos expression in the amygdala and mPFC neurocircuitry activity are

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associated with inducing anxiety. Pharmacodynamic rodent models to assess the anxiety-like behaviors have been used to demonstrate the efficacy of benzodiazepines, SSRIs and SNRIs in reducing anxiety-like behaviors. Table  3.2 describes preclinical rodent models used to model and test pharmacological drugs to treat generalized anxiety disorder. FDA-approved treatments for GAD comprise SSRIs, SNRIs, and benzodiazepines. A study evaluating a panel of SSRIs in FST, TST, light/dark box, foot shock, and social isolation demonstrated the ability of this class of drugs to reduce anxiety-­ related behaviors [107]. First-line treatments for GAD are SSRIs, the side effects of which are listed in section “Major Depressive Disorder”. SSRIs have response rates in treating GAD of around 50–70%, which is compared to placebo response rates around 40–50% [108]. Benzodiazepines, which can be used for acute anxiety treatment, can come with physical and psychological dependence, as well as sedative effects. Drug development for anxiety is focused on treatments for non- or partial-­ responders as well as better overall tolerability and side-effect profiles [109]. Post-Traumatic Stress Disorder Animal models for post-traumatic stress disorder (PTSD) are largely based on exposure to various types of stressors, single or in combination, to elicit more complex neurochemical and behaviroal changes associated with trauma. For example, in PTSD models, physical stressors such as restraint, electric shock, and single prolonged stress are used to examine the response to stress-related cues and re-­exposures to stress. Single prolonged stress exposes the animal to a sequence of stressors, sometimes followed 7–14 days later by re-exposure to a single stressor [110]. The stressors in sequential order are restraint, forced swim, and diethyl ether anesthesia until the animal loses consciousness [111]. The effects of single prolonged stress can be examined using conditioned fear and learning retention paradigms. Social defeat and predator stress are also models used for PTSD. Resident intruder chronic social stress models demonstrate the social avoidance paradigm of PTSD [112]. Predator stress exposes the animals to their species-specific predators, referred to as predator-based psychosocial stress (PPS). PPS studies expose the rodents to a cat or ferret in an unescapable environment. Seven days after exposure, animals are tested in elevated plus maze or light/dark box tests, startle response test, radial arm maze and novel object recognition to assess behavioral avoidance and anxiety-like behaviors in animals [113, 114]. The single-exposure model applies to individuals that acquire PTSD after a single traumatic event. PPS models that translate to repeated exposures use chronic exposure to the predator [113]. Predator scent stress models expose the rodents to inescapable exposure of predator urine, collar, soiled cat litter, and other objects with pheromone-based signatures of the predator. The exposure to inescapable trauma induces many changes in the PFC and hippocampus. There are also increases in activity observed upon SPS exposure in the amygdala, complemented with increases in GABA and glutamate signaling in the striatum. Stress and shock are used to induce PTSD-like symptoms in rodents,

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Table 3.2  Animal models for generalized anxiety disorder Models to induce anxiety-like symptoms Chronic Preclinical Biological neurobiological rodent model rationale/ changes disorder etiology

Repeated unpredictable exposure to mild stressors that are not harmful, to induce anxiety-like behaviors [67, 289–291] Social isolation Isolation as a stressor to induce anxiety or depression-­ like behaviors [291, 294–296] Unpredictable chronic mild stress

Contextual conditioning resulting in decreased latency to lever press or lick after a shock is delivered as a measure of anxiety-like behavior [104, 107] Repeated Chronic exposure to restraint/ immobilization conditions of restraint or immobilization to induce anxiety-like behavior [292] Operant conditioning: punished responding

Model validity

Utilization in drug discovery

FDA-­ approved drugs with demonstrated preclinical efficacy SSRI: Lead Corticosterone ↑ Face: moderate optimization sertraline, [62], escitalopram Construct: Preclinical glucocorticoid SNRI: receptor in mPFC moderate candidate venlafaxine Predictive: selection ↓ [292, 293], BZDs: moderate induces diazepam corticosterone ↑ and anxiety-like behaviors [62]

Disorder etiology Lead optimization Preclinical candidate selection Face: low Disorder Amygdala and mPFC activity↑ Construct: etiology moderate Lead [62], and Predictive: optimization amygdala and Preclinical mPFC expression high candidate in c-fos selection expression↑ [62] DAT activity, DA Face: low release, and D2R Construct: moderate activity↑ [297] Predictive: low

Corticosterone in PFC ↑ [62], glucocorticoid receptor expression in PFC ↓ [292], Female↑ plasma cortisone and Male ↑ pyramidal neuron activation [62, 298]

Face: moderate Construct: moderate Predictive: moderate

SSRI: sertraline SNRI: duloxetine

SSRI: paroxetine

Lead SSRI: optimization fluoxetine Preclinical candidate selection

(continued)

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Table 3.2 (continued) Pharmacodynamic models to assess anxiolytic-like actions of test compounds Model Utilization FDA-­ Preclinical Biological Anxiolytic-­ in drug rodent model readout induced neural validity approved discovery circuitry drugs with changes demonstrated preclinical efficacy SSRI: Early Face: Elevated plus Total time spent Iba-1 pPI3K/ Escitalopram maze in opened arms PI3K and pAkt/ moderate hit-to-lead SNRI: on an elevated Akt expression, Construct: Lead optimization Venlafaxine low IL-6, IL-1β, surface as a Predictive: NF-κB and measure of moderate TNF-α in PFC anxiety-like and in HIP ↓ behavior [62, [289] 107, 299] SNRI: Early Open field test Total time spent Changes in 5-HT Face: Venlafaxine moderate hit-to-lead in open field as and 5-HIAA Construct: Lead expression a measure of optimization low female in PFC anxiety-like and hippocampus Predictive: behavior [62, low 105, 300, 301] ↑, DA an 5-HT increase in HPC ↑ [302] SNRI: Face: low Early Light/dark box Total time spent ↓ pERK1/2 and Venlafaxine Construct: hit-to-lead in dark or light pCREB in Lead hippocampus and low arena as a Predictive: optimization PFC [303] measure of moderate anxiety-like behavior [62, 100, 107, 301] Marble burying Placement of a marble to observe burying as a measure of anxiety [101, 289, 290]

Iba-1 pPI3K/ PI3K and pAkt/ Akt expression, IL-6, IL-1β, NF-κB and TNF-α in PFC and in HIP ↓ [289]

Face: low Construct: low Predictive: moderate

SSRI: Early Sertraline, hit-to-lead Escitalopram Lead optimization

Abbreviations: DAT dopamine transporter, DA dopamine, D2R D2 dopamine receptor, HIP hippocampus, Iba-1 ionized calcium binding adaptor molecule 1, IL interleukin, mPFC medial prefrontal cortex, NF-κB nuclear factor kappa B, pCREB phosphorylated cAMP response element-binding protein, PFC prefrontal cortex, PI3K phosphoinositide 3-kinase, SNRI serotonin/norepinephrine inhibitor, SSRI selective serotonin reuptake inhibitor, TNF-α tumor necrosis factor alpha

and the functional readouts include hiding in assays such as elevated plus maze, open field, and light dark box, as well as EEG and novel object recognition to evaluate PTSD-induced disturbances on sleep and cognition, respectively. Table 3.3 describes preclinical rodent models used to model and test pharmacological drugs to treat post-traumatic stress disorder.

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Table 3.3  Animal models for post-traumatic stress disorders (PTSD) Models to induce PTSD-like symptoms Acute and/or Preclinical Biological chronic rationale/ rodent neurobiological disorder model changes etiology

Single prolonged stress

Chronic social stress

Electric shock

Predator-­ based psychosocial stress

Exposure to a sequence of stressors to measure conditioned fear and learning retention [115, 304–306] Repeated exposure to social defeats, to induce anxiety and social avoidance behaviors [309–311] Tests freezing behavior as a measure of cue related response [310, 311, 313, 314]

Safe, inescapable exposure to species specific predator to induce anxiety-like and PTSD-­ like symptoms [304, 305, 317, 318]

Acute: PFC activity↓, amygdala activity↑, and striatum activity↑ [307, 308] EEG low gamma and delta power↑, and high gamma power ↓ during light phase [308] Chronic: Mesolimbic dopamine circuit expression of BDNF↑ [312]

Acute: c-fos in PFC↑ [115], GSK3 Β/AKT in hippocampus and Amygdala↑ [315], CA1 & CA3 volume ↓ in hippocampus & PFC, and GABA↑ and glutamate↑ in hippocampus [316] Chronic: DA and 5-HT concentration in hippocampus & PFC↓ [319]

Model validity

Utilization in drug discovery

Early Face: moderate hit-to-lead Construct: moderate Predictive: low

FDA-­ approved drugs with demonstrated preclinical efficacy SSRI: paroxetine, seratraline

Early Face: moderate hit-to-lead Construct: moderate Predictive: low

SSRI: paroxetine

Early Face: moderate hit-to-lead Construct: low Predictive: low

SSRI: paroxetine

Face: moderate Construct: moderate Predictive: low

SSRI: Early paroxetine, hit-to-lead sertraline Lead optimization

(continued)

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Table 3.3 (continued) Early Face: Chronic: DA and SSRI: Safe, moderate hit-to-­ 5-HT signaling in, paroxetine, inescapable Construct: leadLead hippocampus & sertraline exposure to PFC dendrite length moderate optimization scent of Predictive: [319] species-­ low specific predator to induce anxiety-like and PTSD-­ like symptoms [115, 311, 318, 320] Pharmacodynamic models to assess anti-PTSD-like actions of test compounds Utilization FDA-­ Anxiolytic-induced Model Preclinical Biological validity in drug readout neural circuitry rodent approved discovery changes model drugs with demonstrated preclinical efficacy SSRI: Light/dark Total time Face: low Early ↓ pERK1/2 and paroxetine box spent in dark pCREB in Construct: hit-to-lead or light arena hippocampus and low as a measure PFC [303] Predictive: moderate of anxiety-­ like behavior [314, 321] SSRI: Early Face: Perirhinal cortex, Novel object Time paroxetine moderate hit-to-lead parahippocampal recognition exploring a Construct: Lead cortex, and novel object moderate optimization as a measure entorhinal cortex activation mediates Predictive: of cognition low and memory the task [323] [113, 305, 322] SSRI: Early Face: EEG Measures the Right frontal theta paroxetine rhythm [325], local moderate hit-to-lead electrical Construct: Lead activity of the field potentials ↓ moderate optimization [326] brain [305, Predictive: 324] low Predator scent stress

(continued)

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Table 3.3 (continued) Elevated plus Total time maze spent in opened arms on an elevated surface as a measure of anxiety-like behavior [107, 299, 306, 318] Open field Total time test spent in open field as a measure of anxiety-like behavior [300, 301, 306, 320]

Early Face: moderate hit-to-lead Construct: low Predictive: moderate

SSRI: paroxetine, sertraline

Early c-fos in PFC NAc Face: and striatum ↑ [328] moderate hit-to-lead Construct: low Predictive: low

SSRI: paroxetine, sertraline

c-fos in cingulate cortex, medial amygdala, hippocampus ↑ [327]

Abbreviations: 5-HT serotonin, BDNF brain-derived neurotrophic factor, DA dopamine, GABA gamma aminobutyric acid, GSK3B glycogen synthase kinase 3B, HDAC-5 histone deacetylase 5, NAc nucleus accumbens, NE/DA norepinephrine/dopamine, NMDA N-methyl-D-aspartate, PFC prefrontal cortex, SNRI serotonin/norepinephrine inhibitor, SSRI selective serotonin reuptake inhibitor, TCA tricyclic antidepressant, VTA ventral tegmental area

FDA-approved therapies for PTSD include SSRIs (sertraline and paroxetine). In mice exposed to foot shock, paroxetine was found to prevent symptom reactivation after extinction training. This was measured in a cue-dependent conditioned freezing assay and by behavioral avoidance tests such as elevated plus maze [115]. The side effects of SSRIs are listed in section “Major Depressive Disorder”. Access to treatment, particularly in veterans who comprise a major portion of PTSD patients, is a major barrier, as less than one-third of veterans needing mental health services are receiving evidence-based care [116]. The response rate to pharmacological treatment in PTSD is around 60%, with only 20–30% achieving full remission [116]. In addition, SSRIs treat the negative emotional states in PTSD but do not treat the hyperarousal. Current drug discovery is focused on drugs with novel mechanisms which show greater efficacy across PTSD symptoms [117]. Schizophrenia Spectrum and Other Psychotic Disorders Animal models for schizophrenia include drug-induced, genetic, and developmental models. Developmental models comprise environmental causes and drug exposure during pregnancy or neonatal stages. Neonatal lesions, specifically, induce abnormalities that present with schizophrenia—in particular, social avoidance, and elevated aggression [118]. A prenatal developmental model exposes pregnant rats to methylazoxymethanol (MAM) between gestational days 15–17 to induce psychotomimetic symptoms in offspring [119, 120]. The model was confirmed by behavioral

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models such as social avoidance, amphetamine-induced hyperlocomotion, and a decrease in PPI [121]. Drug-induced models for schizophrenia commonly use MK-801, an NMDA receptor antagonist, and amphetamine, a dopamine releaser. MK-801, ketamine, phencyclidine, and other NMDA receptor antagonists induce psychotomimetic activity in rodents [122, 123]. Amphetamine increases dopamine activity and therefore induces psychotomimetic-like behaviors as well [124]. Genetic models of schizophrenia consist of numerous gene candidates that contribute to dopamine signaling, neuronal and synaptic plasticity, synaptogenesis, and glutamatergic function. Dysfunction of the gene disrupted-in-schizophrenia 1 (DISC1) and a deletion in 22q11.2 chromosome position are a few genetic models used to study schizophrenia. DISC1 mutations in male mouse models resulted in hyperactivity in open field tests and increased social avoidance while female mice exhibited decreased spatial memory and increased aggression [125]. The 22q11.2 chromosome deletion in mice is designed to translate to the naturally occurring human 22q11.2 chromosome deletion in the clinic [126]. This animal model recapitulates PPI deficits, spatial memory deficits, and fear conditioning modifications observed in individuals with 22q11.2 chromosome deletions [127]. Induced pluripotent stem cells (iPSCs) isolated from humans and differentiated into neurons have allowed researchers to identify relevant genetic mutations and determine differences in neurobiology contributing to the schizophrenia of individual patients [128]. Pharmacological studies using iPSCs have also been useful in understanding the mechanism of drugs such as loxapine and correlating specific drug treatments with gene modifications [129]. IPSC studies are directly translational as the same gene modifications can be mimicked in rodent animal models and studied to test behavioral, neurobiological, and physiological effects. Other behavioral models for schizophrenia are social interaction and working memory [130]. Social interaction in schizophrenia is tested in an open arena containing another unfamiliar animal. Aggression can be measured using social stress paradigms. Working memory is tested using a Y maze. More details on behavioral tests used in schizophrenia can be found in the following review [130]. A detailed overview of these animal models of schizophrenia is presented in Table 3.4. FDA-approved antipsychotics such as clozapine, haloperidol, olanzapine, risperidone, amisulpride, and aripiprazole are efficacious in reversing ketamine-­ induced deficits in PPI [131]. Clozapine also restored ketamine-induced deficits in working memory and attenuated ketamine-induced hyperlocomotion [132]. First generation antipsychotics cause extrapyramidal side effects including rigidity, tremors and uncontrolled muscle movements, while second-generation antipsychotics have decreased extrapyramidal side effects but still have sedating and endocrine side effects in 86% of patients [133]. Treatment resistance to at least two medications occurs in 34% of patients [134]. In addition, treatments for schizophrenia treat only the positive symptoms, and have little efficacy on negative or cognitive symptoms, leading to recent drug discovery efforts in these domains.

MAM during fetal development

Neurodevelopmental models Neonatal ventral hippocampal lesions

Hippocampal pathology in schizophrenia with adolescent onset of symptoms; hippocampal disconnection model, cause locomotion ↑ [330, 331] Neurodevelopmental hypothesis of schizophrenia. Alteration of parvalbumin neurons in schizophrenia patients [335], causes spontaneous locomotor activity ↑ [121], PPI ↓ [121]

Chronic pharmacologic models Chronic phencyclidine NMDA receptor hypofunction

Models to induce schizophrenia-like symptoms Preclinical rodent Biological rationale/disorder model etiology

Table 3.4  Animal models for schizophrenia

PFC neuron excitability ↑ [336], cortical thickness ↓ [121], ventricular size ↑ [121], loss of parvalbumin interneurons in PFC and ventral subiculum [337]

D2 dopamine receptor ↓ [332, 333], cortical disinhibition [334]

Hypofrontality, parvalbumin interneurons ↓ [329]

Chronic neurobiological changes

Face: low Construct: moderate Predictive: moderate Face: moderate Construct: moderate Predictive: moderate

Face: low Construct: high Predictive: high

Model validity

Lead optimization

Lead optimization

Lead optimization

Utilization in drug discovery

Typical APDs: haloperidol Atypical APDs: clozapine

Typical APDs: haloperidol, Atypical APDs: clozapine, olanzapine, and risperidone

Atypical APDs: clozapine, risperidone

FDA-approved drugs with demonstrated preclinical efficacy

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Association with schizophrenia populations [349], impaired cortical development [350], causes PPI ↓

Association between 22q11.2 microdeletion and schizophrenia [342, 343], causes PPI ↓

PFC dopamine innervation ↓ [351]

Hippocampal volume ↓ [344, 345], COMT ↓ [346], DOPAC in PFC and striatum ↑ [347, 348]

NAc dopamine ↑, PFC dopamine ↓ [339–341]

Pharmacological models Amphetamine-induced Amphetamine hyperlocomotion and NAc dopamine ↑↑ changes PPI deficits are psychotomimetic [352, 353]

DISC1 mutation

Genetic models 22q11.2 deletion

Environmental models Isolation rearing Early life environment impact on development of schizophrenia, causes PPI ↓, hyperlocomotion, auditory gating ↓ [338]

Face: moderate Construct: moderate Predictive: moderate

Face: moderate Construct: high Predictive: moderate Face: moderate Construct: high Predictive: moderate

Face: moderate Construct: moderate Predictive: moderate

Early hit-to-lead Lead optimization

Lead optimization

Lead optimization

Lead optimization

(continued)

Typical APDs: chlorpromazine, haloperidol, perphenazine Atypical APDs: aripiprazole, sertindol, olanzapine, clozapine, remoxipride, risperidone, ziprasidone

Atypical APDs: clozapine

Typical APDs: haloperidol, Atypical APDs: clozapine

Atypical APDs: clozapine, ziprasidone

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NMDA receptor antagonists cause hyperlocomotion and PPI deficits which are psychotomimetic [354, 355]

NAc dopamine ↑

Inhibition of startle response [352]

Pre-pulse inhibition

Face: low Construct: moderate Predictive: moderate Face: high Construct: moderate Predictive: moderate

NAc dopamine ↓

NAc dopamine ↓

Model validity

Face: moderate Construct: moderate Predictive: moderate

Early hit-to-lead Lead optimization

Utilization in drug discovery Early hit-to-lead Lead optimization

Early hit-to-lead Lead optimization

FDA-approved drugs with demonstrated preclinical efficacy Typical APDs: haloperidol, eticlopride Atypical APDs: aripiprazole, clozapine, sertindol, olanzapine, risperidone Typical APDs: chlorpromazine, haloperidol, perphenazine Atypical APDs: clozapine, olanzapine, remoxipride, risperidone, sertindol, ziprasidone

Typical APDs: eticlopride, chlorpromazine haloperidol Atypical APDs: clozapine, olanzapine, remoxipride, risperidone, sertindol, ziprasidone

Abbreviations: APD antipsychotic drug, DISC1 disrupted in schizophrenia 1, MAM methylazoxymethanol acetate, NAc nucleus accumbens, NMDA N-methyl-­ D-aspartate, PFC prefrontal cortex, PPI pre-pulse inhibition

Locomotor activity [352–355]

Hyperlocomotion

Acute pharmacodynamic models to assess antipsychotic-like actions of test compounds Preclinical rodent Biological readout APD-induced acute model neurobiological changes

NMDA receptor antagonist-­ induced changes

Table 3.4 (continued)

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Substance-Related and Addictive Disorders There are many types of addictive disorders. Substance use disorders (SUDs) comprise, among others, alcohol, psychostimulants, opioids, benzodiazepines, and nicotine. Each area employs specific animal models to test the different stages and characteristics of different addictions, though some models are shared across types of addictive disorders. Addiction animal models can be conducted using noncontingent (involuntarily administered) treatment with substances of abuse or contingent (self-administered) drug administration, with each method examining different aspects and dynamics of addiction. Behavioral sensitization is a noncontingent model based on the theory that repeated noncontingent administration of a drug induces drug cravings [135]. Behavioral sensitization occurs in two phases. The induction phase changes neurobiological mechanisms, while the expression phase displays the behaviors involved as a result of the neurobiological changes [135–137]. After a period of extinction of administration of an opioid, illicit drug, nicotine, or ethanol, a drug challenge test is facilitated to test the expression of behavioral sensitization. Most addiction studies apply the behavioral sensitization theory to their approach to understanding the neurobiology of the illness as well as the behavioral manifestations of the changes in the neurobiology during the induction phase. Conditioned place preference (CPP) is a popular model to study reward processes. Noncontingent administration studies using CPP pair drug administration with a distinct location where this reward occurs, such as dosing a mouse with opioid and isolating them in a particular compartment of a box. Repeated administration of a drug of abuse induces a preference for the drug-associated compartment over the non-reward associated compartment [138]. The time spent in each compartment is compared to determine preference [138]. Extinction following CPP is used to test relapse and reinstatement in drug studies. Contingent dosing can be assessed using self-administration (SA) to assess drug-­ seeking, addiction potential, reinstatement, and expression. SA is an operant response task that requires an action from the animal to receive drug or alcohol treatment. Animals are trained to self-administer the reinforcing drug to analyze the various stages of addiction. SA models are further categorized as short-access and long-access models which differentially study drug-use behaviors associated with recreational drug use versus long-term effects, respectively [139, 140]. Operant schedules can be applied to SA models using fixed ratio (FR) and progressive ratio (PR) schedules. FR schedules deliver the drug, alcohol, or sucrose after a fixed number of responses have been completed. The PR schedule increases the required number of interactions with each reinforcement earned in order to examine motivational aspects of self-administration and reward strength of a reinforcing drug. These schedules can be paired with cues and periods of extinction to study reinforcement and relapse in each schedule. Preclinical animal models and pharmacodynamics models for SUDs comprise models to observe reward and motivation. Changes in the mesolimbic circuitry are established as the underlying neurobiology that contributes to drug-seeking

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behavior. Table 3.5 describes the models and relevant FDA-approved drugs used to treat substance use disorders. SA models and CPP models are used to study the effects of drug treatments on expression, reinstatement, and relapse of addiction. Currently approved treatments for SUDs are limited and include methadone, buprenorphine, and naltrexone for opioid use disorder. Naltrexone in mouse models inhibits methamphetamine-­ induced hyperlocomotion, expression of CPP, and methamphetamine-cued reinstatement in CCP [141]. These treatments are approved for acute overdose and maintenance of opioid use disorder, including withdrawal symptoms and cravings. However, these treatments face issues with controlled dispensing, addiction potential, high relapse rates, and tolerance. Outside of opioid use disorder, other substances don’t have many options for pharmacological treatment. In addition, access to treatment remains a major barrier, with a particularly large unmet need in homeless populations [142]. Drug discovery for treatments for SUD is focused on decreasing relapse rates, lowering addiction potential, and improving efficacy in other substance use disorders besides opioids. Table 3.5  Animal models for substance use disorders SUD treatment-­ induced acute Preclinical Biological neurobiological rodent model readout changes Intravenous Operant Agonists self-­ response task stimulate administration that requires an increased Fixed ratio action to dopamine release Progressive receive drug or to compensate for ratio alcohol hypofunction, treatment to antagonists assess decrease addiction dopamine release [356–359] by drugs of abuse [360, 361] Conditioned The time spent Agonists cause place in the CPP because they preference reward-­ increase associated dopamine, compartment agonists cause used to assess CPA because they acquisition, decrease relapse, and dopamine [364, reinstatement 365] [362, 363]

FDA-approved drugs with Utilization demonstrated Model in drug preclinical validity discovery efficacy Face: high Disorder Mu-opioid Construct: etiology receptor moderate Early agonists: Predictive: hit-to-lead buprenorphine high Lead and methadone optimization Mu-opioid Abuse receptor potential antagonists: naltrexone

Face: moderate Construct: moderate Predictive: moderate

Disorder etiology Abuse potential

Mu-opioid receptor agonists: buprenorphine and methadone Mu-opioid receptor antagonists: naltrexone

Abbreviations: 5-HT serotonin, CPA conditioned place aversion, CPP conditioned place preference, VTA ventral tegmental area

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Attention Deficit Hyperactivity Disorder Examples of animal models for ADHD are genetic models, the spontaneously hypertensive rat (SHR) model, and prenatal ethanol exposure models. Impulsivity, inattentiveness, and hyperactivity are the three hallmark behaviors of ADHD. The dopamine transporter knockout (DAT-KO) mouse model is based off the various DAT mutations that have been observed in humans with ADHD. DAT-KO models exhibit hyperactivity, increased spontaneous dopamine cell firing, and deficits in spatial memory [143–145]. Tachykinin-1 (NK1) KO mice displayed hyperactivity, impulsiveness, and inattentiveness, which can also be induced in wild-type mice using NK1 antagonists [146, 147]. Hyperactivity in NK1 models can be inhibited via psychostimulants [147]. SHR is a strain of inbred Wistar-Kyoto rats that display hyperlocomotion, impulsivity, and other key symptoms of ADHD [148–150]. Delay discounting tests are used to test impulsivity in ADHD rodent models resulting in the choice of the immediate reinforcers regardless of the larger reward obtained by delayed reinforcement [151]. The five-choice serial reaction time (5-CSRT) task is used to test attentiveness; in this assay, animals need to respond to the location of a light cue after variable delay periods to earn a food reward [152]. First-line ADHD treatments include psychostimulants such as methylphenidate and amphetamine, which treat impulsivity, hyperactivity, and inattention. Second-­line treatment includes atomoxetine, an SNRI. Atomoxetine and methylphenidate were tested using 5-CSRT in Long-Evans rats and were shown to improve attentiveness and impulsivity [153]. Methylphenidate and l-amphetamine tested in adolescent SHR rats reduced hyperlocomotion and impulsivity using the 5-CSRT test [154, 155]. A third of patients don’t respond to psychostimulants and are thus treated primarily with atomoxetine, which has a smaller effect size [156]. Psychostimulants can be addictive and thus face strict controls. Drug discovery for ADHD is focused on improved efficacy and decreased abuse liability. ADHD preclinical genetic models produce changes in dopamine tone and increases in hyperactivity and impulsivity. DAT mutations, for example, alter DAT expression and activity. Pharmacodynamic models to test the efficacy of drugs to reduce hyperactivity and impulsiveness with high validity are 5-CSRT and open field test. FDA-approved drugs have been validated in these models to demonstrate a decrease in dopamine tone, hyperactivity, and impulsivity. Table  3.6 describes preclinical rodent models used to model and test pharmacological drugs to treat ADHD.

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Table 3.6  Animal models for attention deficit hyperactivity disorder (ADHD) Models to induce ADHD-like symptoms Preclinical Biological Chronic rodent rationale/ neurobiological model disorder changes etiology

Model validity

Utilization in drug discovery

FDA-approved drugs with demonstrated preclinical efficacy SHR Genetic model Hyperactivity and Face: high Disorder CNS Stimulant: to induce dopamine Construct: etiology amphetamine ADHD-like signaling↑ in moderate Early Alpha2A-­ behaviors [366, striatum and NAc Predictive: hit-to-lead adrenergic 367] [368] low Lead receptor agonists: optimization Guanfacine Abuse potential DAT Genetic model Dopamine tone, Face: Disorder CNS Stimulant: mutations to induce impulsivity and moderate etiology amphetamine ADHD-like hyperactivity↑ Construct: Early behaviors [369] [369] moderate hit-to-lead Predictive: Lead low optimization Pharmacodynamic models to assess anti-ADHD-like actions of test compounds Preclinical Biological Stimulant-­ Model Utilization FDA-approved rodent readout induced acute validity in drug drugs with model neurobiological discovery demonstrated changes preclinical efficacy Five-choice Nose-poke ↑mPFC activation Face: Disorder CNS Stimulant: serial upon visual for action control moderate etiology methylphenidate reaction stimulus to [370] Construct: Lead Norepinephrine time earn a food moderate optimization Reuptake (5-CSRT) reward as a Predictive: Inhibitor: measure to test moderate atomoxetine attentiveness and impulsivity [152, 153] Open field Total time ↑c-fos in most Face: low Lead CNS Stimulant: test spent in open brain regions, ↑ Construct: optimization methylphenidate field as a dopamine in the moderate Norepinephrine measure of dorsal and ventral Predictive: Reuptake hyperactivity striatum [328] moderate Inhibitor: [366, 371] atomoxetine Abbreviations: CNS central nervous system, NAc nucleus accumbens

3.2.4 Other Clinical Considerations to Modeling Psychiatric Disorders in Animals: Sex, Age, Ethnicity Sex, age, and ethnicity are examples of factors that impact the validity of an animal model. Sex differences in animal models include differences in metabolism, estrogen-­regulated neuronal and physiological processes, symptomatic behaviors,

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and response to treatment. Estrogen receptor alpha (ERα) and estrogen receptor beta (ERβ) have been shown to have differences in expression depending on the brain region. ERα and ERβ have been found in the prefrontal cortex, temporal cortex, sensory motor areas, hippocampus, and the cortico-striato-thalamo-cortico (CSTC) circuit [157–163]. Age differences have various impacts on the behavior of the animals as the neurocircuitry changes, which also likely induces changes in response to treatments [164, 165]. The neurobiology and circuitry in the aged brain are different from the nonpathological adult brain, suggesting that there would be changes in the pharmacodynamics and efficacy of some psychiatric treatments [164]. Changes in neurocircuitry in the aging brain affect several brain areas and involve the dopaminergic, glutamatergic, and cholinergic transmitter systems [166–168]. Although there are more factors to consider, those mentioned above encompass some key factors to be considered with respect to animal model variability and reproducibility. Confounding results and reproducibility are highly likely in the case of poor modeling. Thus, proper protocols with specific outlines of the factors that are key to each model should be provided. Below are examples of how sex, age, and ethnicity influence symptomatology, treatment response, and pharmacokinetics in human and animal models. Sex and Age Differences in Symptomatology of Psychiatric Illnesses Sex- and age-related differences in prevalence and symptoms exist across all psychiatric illnesses. MDD has a higher incidence in women than in men, and mood symptoms and MDD episodes are increased during periods of low estrogen hormone levels [169]. Atypical symptoms are also increased in women with MDD compared to men [170]. Men experience more anhedonic symptoms in MDD, but women experience more anxiety [171, 172], and the presence of other depressive symptoms such as insomnia, appetite, and aggression is affected by estrogen [173]. In females, age-related changes in estrogen levels affect MDD symptoms. For example, MDD episodes and mood symptoms increase during and after menopause in women [169]. Sex-related differences are also seen in animal models of depression, such as the FST. FST in female rodents revealed an increase in immobility duration, while differences in latency to immobility are inconsistent across studies [174, 175]. In a learned helplessness model of escape following inescapable shock, female rats had faster escape times, contrary to what was seen in FST immobility [176, 177]. There is a more robust decrease in sucrose intake in male rats compared to female rats following chronic mild stress exposure [178]. These rodent phenotypes are largely consistent with the human data showing that men experience greater anhedonia and women experience greater anxiety [171, 172]. Sex- and age-related differences are demonstrated in schizophrenia as males have an earlier onset and an overall higher incidence of schizophrenia [179]. In

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contrast, women have less severe negative symptoms but higher levels of affective symptoms [179]. The major sex-related differences reported in post-traumatic stress disorder (PTSD) are driven by the difference in circulating hormones in men and women. Estrogen cycles in women are directly linked to changes in circulating cortisol, affecting female sensitivity to events that cause PTSD and the development of anxiety as a result of a traumatic event [180, 181]. Women are twice as likely to develop PTSD compared to men [181]. In rodent models of PTSD, female rats recapitulated the overall increased vulnerability to developing the illness. Compared to male mice, females have a decrease in fear conditioning but an increased startle response (assays described in more detail in section “Post-Traumatic Stress Disorder”) [181–183]. Sex and Age Differences in Response to Psychiatric Drugs Sex differences in the efficacy of treatment for MDD patient populations were demonstrated by showing that the selective serotonin reuptake inhibitor (SSRI) sertraline was more efficacious in women than the tricyclic antidepressant (TCA) imipramine, whereas in men, imipramine resulted in greater treatment response [184]. Similarly, female MDD patients experiencing atypical symptoms responded more favorably to SSRIs or monoamine oxidase inhibitors (MAOIs) than TCAs, while the opposite responses were observed in male MDD patients [185]. In female patients with schizophrenia, superior treatment responses to antipsychotics were observed relative to male patients, particularly with clozapine [186]. Interestingly, in the preclinical model of latent inhibition, a model of learned inattention which is impaired in schizophrenic patients, treatment with haloperidol and clozapine restored impaired latent inhibition, especially during proestrusestrous cycles of female rats.  ex, Age, and Ethnicity Differences in Pharmacokinetics S of Psychiatric Drugs It is well known that there are marked differences in the way distinct patient populations may respond to the same psychiatric medication. Since a comprehensive coverage of this topic is beyond the scope of this chapter, we will focus here on the way the clinical response to treatment can be affected by sex-, age-, and ethnicity-­dependent changes in drug pharmacokinetics. A drug’s absorption, distribution, metabolism, and excretion (ADME) properties determine if a drug (1) reaches its site of action, in the case of a psychiatric drug, the brain, (2) the brain levels that a drug reaches, and (3) a drug’s duration of action. Since many drugs are metabolized by cytochrome p450 (CYP) metabolic enzymes, differences in the expression of CYP isoforms across patient populations can differentially

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impact drug efficacy. Examples are CYP3A, the main CYP isoform which is more highly expressed in liver microsomes from females than males [187], and CYP1A2, an enzyme metabolizing  many antipsychotic drugs, both of which have been suggested to have higher expression in females than in males and also to be influenced by age [188, 189]. Finally, CYP2D6 and CYP2B6 are enzymes that metabolize drugs used to treat psychiatric illnesses [190, 191]. Imipramine, a CYP2D6 substrate, has been shown to be metabolized faster in females than in males [191]. Furthermore, CYP2B6 polymorphisms which alter metabolic rate are influenced by sex and ethnicity [192]. Body weight, organ size, and percent body fat influence metabolism, such that patients with lower body weight responded better to SSRIs than heavier patients. Finally, females have a lower expression of the transporter protein p-glycoprotein, reducing the efflux of antidepressants in the gut and increasing the uptake of antidepressants across the blood-brain barrier [193, 194]. Ethnic differences are also seen in the distribution, activity, and expression of metabolic enzymes, such as CYP2D6 enzyme expression [195]. These differences result in differential metabolism of drugs by influencing the half-life, drug-drug interaction, and plasma and drug concentrations, thereby changing the efficacy of these drugs. To model ethnic differences, models of genetic variations in CYP enzymes are needed to assess pharmacokinetic changes to further understand differences in responses to treatment for psychiatric disorders. Use of Female Animals for Drug Discovery in Psychiatric Disorders Collectively, it is critical that both male and female animals are used not only to model the mechanisms underlying psychiatric illnesses, but the response to and efficacy of psychiatric medications. Sex differences in rodents change over the life span of the animals as estrogen levels change. Changes in the estrous cycle in female rodents, for example, have been shown to modulate behaviors related to the symptomatology of MDD [169, 196, 197], generalized anxiety disorder (GAD) [169, 196, 197], PTSD [169, 196, 197], substance use disorders (SUDs) [197], attention deficit hyperactivity disorder (ADHD) [196], and others [196, 197]. Although estrogen cycles and menopause are not directly translational in all rodent species (e.g., female mice do not undergo menopause, only estrous pause with aging), models using intact and ovariectomized female rats and mice have provided important data on the differences in onset of symptoms, mood fluctuations, and metabolism. Furthermore, the use of female models has recapitulated many important differences in the drug responses for psychiatric illnesses observed between male and female patients [197]. Hence, the use of female rodents in animal models for drug discovery is critical for detecting potential differences in treatment response in female patient populations.

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3.3 Utility of Animal Models Throughout the Stages of Modern Drug Discovery Stages 3.3.1 Target Identification and Validation As discussed in the previous sections, animal models have been and continue to be essential for understanding basic biology and developing effective treatments for psychiatric disorders. The use of animal models particularly in drug discovery requires moderate to high validity models to ensure that the effects can be recapitulated in humans effectively and safely. As shown in Fig. 3.1 and discussed below, animal models of various psychiatric disorders are used throughout the different stages of the drug discovery process. In the earliest stage, validation of a novel target for drug discovery involves establishing a strong link between the target and the disease indication for which a drug is being developed. In animal models used in drug discovery, one of the first steps is establishing gene sequence homology for the target across species of interest. If target homology is low between humans and the preclinical species, preclinical data may not accurately translate into the clinic. Sequence homology is a key factor that determines the selection of a primary preclinical species. Animal models in target validation are critical for understanding the

Fig. 3.1  Animal models used in the stages of psychiatric drug discovery. Critical information is gleaned from animal models throughout the different stages of drug discovery, facilitated by the choice of model and its validity. Target identification and validation prioritize models with high construct validity to establish the relationship between the target and the psychiatric disorder. During the high-throughput screen/hit-to-lead stage, higher throughput in vivo models with strong predictive validity for engagement of the target are prioritized, in order to quickly screen large numbers of compounds and establish early PK/PD relationships. Early lead optimization prioritizes construct and face validity as the in  vivo efficacy in preclinical models of the psychiatric disorder are established. Late lead optimization prioritizes predictive and face validity as more in vivo efficacy is examined and translatability is the key concern. Selection of preclinical candidate involves a robust use of a variety of animal models with various validities, especially construct validity as the full preclinical package is developed. Abbreviations: PK Pharmacokinetics, PD Pharmacodynamics

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target expression and distribution, throughout the CNS and the periphery, on the level of both tissue and cellular and subcellular localization. In psychiatric animal models, the expression of a target within a disease-relevant cell population in the CNS is critical for target identification. In addition, animal models are often used to establish the relationship between the target and the disease state by manipulating the target and examining disease-relevant outputs, using genetic or pharmacological manipulation, if the pharmacological tools exist. Understanding the expression, distribution, and disease-relevant function of a target in animal models before beginning the process of developing a drug can prevent a large waste of resources on an inadequately validated target. Genetic knockdown or knockout models are often used to validate the relevance of a target to a particular disease state. In the investigation of M5 muscarinic acetylcholine receptor antagonists for the treatment of substance use disorders (SUD), the first indication that this might be a viable target was its expression in the mesolimbic circuitry. M5 is the only muscarinic receptor found in the ventral tegmental area (VTA), an area rich in dopamine neurons that play a role in reward processing and are a key substrate for the actions of substances of abuse [198, 199]. Generation of the M5 knockout mouse [200] allowed for examination of the effects of decreased M5 function on substance-use relevant behaviors and showed that these mice have decreased responsiveness to morphine-conditioned place preference [201], decreased cocaine self-administration at low doses [202], and reduced morphine-­ induced hyperlocomotion [203]. Collectively, these data from the knockout model provide evidence that modulation of M5 may be a viable path for treatment of SUDs, showing validation for this target. A well-validated drug target with an established role in disease prevents many potential problems from arising in later stages of drug discovery, particularly in terms of clinical efficacy.

3.3.2 High-Throughput Screening/Hit-to-Lead High-throughput screening involves an assay which can process a large number of compounds very quickly, with an easily readable output. This output can be functional, such as a calcium mobilization screen for a Gq-coupled G-protein coupled receptor (GPCR), or binding-based, such as radioligand displacement. Compounds that have a positive response during the high throughput screen are referred to as hits. Hit-to-lead is the stage of drug discovery that involves further analysis of these hits for validation and to assess which of multiple hits are the best prospects for continued development. These compounds with promising properties are referred to as lead compounds or lead chemical series. Most high-throughput screening and hitto-lead is performed in vitro, but that does not mean that animal models do not have a critical role to play. The major role of animal models in these early drug development stages is in pharmacokinetic modeling. During hit-to-lead, in vivo pharmacokinetic basics are established, such as clearance, half-life, and brain penetrance. Exposure in both the plasma and the target tissue (the brain, for neuropsychiatric disorders) are established. In addition, in vitro-in vivo correlations are examined.

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3.3.3 Early-, Mid-, and Late-Lead Optimization Lead optimization involves taking the lead compounds or series from the hit-tolead phase of drug discovery and improving the drug-like properties of the molecules. Lead optimization is often separated into early-, mid-, and late- stage lead optimization. Assays used in the early lead optimization stage are selected for high predictive validity related to the target mechanism under investigation wherever possible. For example, in the development of a novel treatment for depression, a compound may first be analyzed in the FST [56], which in addition to high predictive validity for classical antidepressants, also has relatively high throughput and can therefore be used for rapid screening of the acute effects of many compounds. However, it is worth noting that ruling out a drug based on a negative result in an assay with high predictive validity and low face/construct validity is ill-advised when working with a novel mechanism. If an assay, such as forced swim, is validated based on the mechanism of current treatments, a drug which may treat the symptoms of depression by a novel mechanism may show a negative result in this assay, but a positive result in other assays. Along with the first efficacy measure in vivo, animal models are also used to further understand the pharmacokinetics of early-stage compounds. This process also involves gaining an early understanding of the pharmacokinetic to pharmacodynamic relationship of key ligands. It must also be established that systemic administration of early compounds results in sufficient target tissue exposure to observe the desired effects. During the progression from mid- to late-lead optimization, lead compounds undergo further pharmacokinetic profiling and advance into broader efficacy evaluations. By late lead optimization, compounds must have high selectivity for the target and adequate bioavailability in both the selected primary and higher-order animal species for future toxicology studies. Lead compounds are also evaluated in multiple lower-throughput models with higher etiological (construct) and face validity. For example, in the later development of a novel antidepressant drug, such models might include the unpredictable chronic mild stress model and/or chronic social stress models (described in section “Major Depressive Disorder”) [204]. The relationship between stress, anhedonia, and depression is clear in humans [205], making the construct validity of this model better than an assay like forced swim. Meanwhile, the face validity in terms of decreased rewardseeking is high and can be assessed via alterations in food intake, sucrose preference, and/or intracranial self-stimulation (described in section “Major Depressive Disorder”). A combination of models with different validities allows for a full profile of the lead series in 2–4 animal models of efficacy for the related psychiatric disorder, including genetic and behavioral models, as well as efficacy versus side-effect profiling to understand the therapeutic index. Translational biomarkers are also used at this stage of drug discovery to understand the dose-related target receptor occupancy and/or changes in measures of functional target engagement, discussed in more detail in Sect. 3.3.5.

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3.3.4 Preclinical Candidate Selection Selection of the preclinical candidate (PCC) involves an extensive use of multiple animal models for the particular psychiatric disorder with various validities, especially construct validity. The effects of chronic dosing alone and in combination with psychiatric medications that potential patient populations may be taking are also evaluated for changes in PK and/or PD effects. Drug-drug interactions are also evaluated in animals to establish the therapeutic index for preclinical candidate molecules. Using higher order species pharmacokinetics, animal-to-human modeling is performed to predict the pharmacokinetic properties and relevant doses for be use for first in human studies. Predictions for margins of safety in dosing are initiated and then completed once the full toxicology package across two species has been finalized during the Investigational New Drug (IND)-enabling studies.

3.3.5 Translational Animal Models for Target Occupancy and Functional Target Engagement for Psychiatric Drug Discovery Imaging A critical aspect of translational drug development is an understanding of the relationship between receptor occupancy, using positron emission tomography (PET), and drug efficacy, referred to as the occupancy-to-efficacy relationship. This means understanding what percentage of receptors need to be engaged by the drug of interest in order to produce a desired behavioral effect. Understanding the occupancy-to-­ efficacy relationship in a preclinical species can provide critical information for the success of a clinical trial, especially when considering which doses to test in humans. If 50% target receptor inhibition is required in order to see antidepressant-­like activity in the forced swim test in rats, then doses that achieve 50% target receptor occupancy in humans during clinical trials should be the initial goal. Alternatively, it may be critical to understand the relationship between changes in a measure of functional target engagement, such as functional magnetic resonance imaging (fMRI), and the efficacy observed in several preclinical species to better inform decisions of dose selection and biomarker utilization in future clinical trials with psychiatric patient populations. fMRI Magnetic resonance imaging (MRI) is an imaging technique that uses magnetic fields, one static and one gradient, in order to locate nuclei within the brain. Standard MRI is used to produce structural images of the brain, while functional MRI (fMRI)

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is used to assess brain activity. One of the major measurements of fMRI assesses the flow of oxygen throughout the brain, a signal referred to as blood-oxygen-level dependent (BOLD) contrast. Regions receiving abundant oxygen are interpreted as more active regions of the brain. Because a majority of energy consumption in the brain is due to glutamate recycling, this BOLD signal correlates with glutamate response and thus is an indirect way of examining functional target engagement at glutamate receptors [206, 207]. An example of BOLD fMRI as a measure of functional target engagement in drug discovery is the NMDAR antagonist ketamine-induced changes in BOLD signal (termed pharmacoBOLD) for measuring glutamatergic receptor functional target engagement when developing drugs for schizophrenia and other psychotic disorders. For example, the mGluR2/3 agonist TS-134 when given in humans produced a robust reduction in ketamine-induced increases in BOLD signal, specifically in the dorsal anterior cingulate cortex [208]. Pomaglumetad, another mGluR 2/3 agonist of lower potency, did not decrease ketamine-induced increases in BOLD signal at the doses that were examined in a failed clinical trial, suggesting a potential reason for this clinical failure  – insufficient functional target engagement. Ketamine-induced changes in BOLD signal can be detected in rats, as well as humans [209], providing strong translational value. Another mGluR 2/3 agonist, LY379268, robustly attenuated ketamine-induced increases in BOLD signal in the cingulate cortex [210], very similar to effects observed in humans. This direct translation of technique from preclinical animal models to humans allows for the use of pharmacoBOLD fMRI in facilitating the preclinical to clinical transition in drug discovery. Understanding the level of functional target engagement required to produce results in models of antipsychotic-like activity allows for the prediction of the levels of target engagement required to treat positive symptoms in human patients. For example, if a drug robustly attenuates 25% of pharmacoBOLD signal in rats at the doses that show efficacy in reversing a stimulant-induced locomotion assay that predicts antipsychotic-like activity, but the clinical trial dose shows no change in the pharmacoBOLD signal in humans, this may indicate that a higher dose is required to see efficacy in humans. PET Compared to fMRI, positron emission tomography (PET) provides a more direct measurement of receptor occupancy. Instead of using magnetic fields, PET imaging occurs by measuring radiation emitted by radiotracers, or radioactive substances that are injected into the body. PET scans then form an image based on the density of the radioactivity in different regions, which correspond to where the radioactive substance is distributed in the tissue. A wide variety of ligands can be used as PET tracers, given that they have sufficient properties to be injected into a living creature and can be labeled with a radioactive atom. Because of this diversity in PET ligands,

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if a PET ligand exists for the receptor under investigation, this can be used as a direct measure of binding of a drug to the receptor of interest. One set of examples of PET and radioligand tools for a receptor of interest is [11C]raclopride and [3H]raclopride [211]. Raclopride is a competitive antagonist selective for D2 dopamine receptors, and it can be radiolabeled with either tritium or carbon-11. By examining the difference in a PET scan with raclopride alone and raclopride in combination with other drugs which bind to D2, raclopride displacement can be measured. If a drug of interest, such as a typical antipsychotic like chlorpromazine, binds to D2 receptors in the same binding site as raclopride, the amount of raclopride binding detected will decrease proportionately to chlorpromazine binding to the D2 receptors, allowing measurement of the amount of D2 receptors occupied by chlorpromazine. Similar methods can be used for PET studies conducted in both humans and animal models such as nonhuman primates or rats, allowing for high translational value. Both [11C]raclopride and [3H]raclopride have been used in humans and rats to examine the levels of D2 receptor occupancy of raclopride that contribute to its antipsychotic efficacy versus the induction of extrapyramidal side effects (EPS). In rats, suppression of the conditioned avoidance response (CAR) was used to predict antipsychotic-­like activity, particularly for activity through D2 receptors [212]. In a comparison study, efficacy with raclopride in suppression of CAR occurred at a D2 occupancy level of 70–75%, where EPS were observed at an occupancy of 80%, demonstrating the narrow window of receptor occupancy for therapeutic effects without side effects [211]. This is similar to results seen in human schizophrenia patients with typical antipsychotic drug haloperidol, where psychotic symptom alleviation became likely at a minimum of 65% D2 occupancy and EPS at 78% receptor occupancy, as measured by [11C]raclopride PET [213]. Interestingly, clozapine, a common atypical antipsychotic, produced a D2 receptor occupancy of 38–63%, demonstrating why atypical antipsychotics show much lower rates of EPS [214]. Understanding the relationship between clinical efficacy, toxicity, and receptor occupancy using PET in preclinical animal species allows for the design of clinical trials in which it can be verified that the selected dose range is correct. If the dose range is promoting the level of receptor occupancy in a PET study which correlated to efficacy in preclinical species, then efficacy in humans would be expected. This can also aid in the prediction of dosages at which side effects would be expected. Overall, understanding receptor occupancy in preclinical species creates much more confidence in the preclinical to clinical transition. Quantitative EEG and Event-Related Potential Measurements Quantitative electroencephalography (qEEG) measures the electrical activity (oscillations) in the brain. Synchronous waves observed in EEG are a summation of alpha, beta, delta, theta, and gamma waves at any given time. Alpha waves (8–13 Hz) are associated with awake relaxed states with low levels of stimulation. Beta waves

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(13–30 Hz) are also associated with wake states, but more focused and stimulated wake states [215]. Theta waves (4–7 Hz) are associated with rapid eye movement (REM) sleep states and light sleep. Delta waves (1–3 Hz) are highly associated with deep, restful sleep. Gamma waves (>30 Hz) are highly associated with wake, deep focus, and problem-solving. EEG is a functional means to measure changes in brain activity to assess sleep, diagnose epilepsy and in pharmacological drug studies. The comparisons of changes in resting power bands to activity related power bands is done through modulation of event-related synchronization (ERS) or desynchronization (ERD) [215]. The two types of EEG studies are spontaneous or resting state EEG, which measure the general activity of the brain, and event-related potential (ERP) studies in response to external stimuli [216]. Changes in EEG signature, sleep-wake states, and circadian rhythms are associated with many psychological diseases. Mammalian qEEG studies are highly translational to humans and provide an effective biomarker for identifying changes in sleep-wake states and associated neurocircuits that are involved [217]. Pharmacological EEG studies provide powerful insights into changes in band power frequencies that indicate alterations in arousal, learning and memory, and consciousness. For example, EEG studies in wild-type Wistar rats compared the sedative, zolpidem, to 5-HT antagonists, RO4368554 (RO), and MDL 100907 (MDL). Zolpidem-induced shorter latency to sleep onset compared to RO and MDL.  All three compounds increased delta power resulting in increases in NREM. However, MDL effects were not as pronounced as RO and zolpidem. These results suggest that 5-HT antagonists may be implicated for insomnia drug development [218]. Understanding the changes that occur in sleep-­wake states in psychological conditions may also allow the future development of treatments that mitigate the progression of the different psychiatric illnesses, including schizophrenia and the behavioral disturbances in Alzheimer’s Disease.

3.3.6 Example of In Vivo Target Validation of the Selective M4 PAM Mechanism for the Treatment of Schizophrenia Muscarinic acetylcholine receptors (mAChRs) are comprised of five subtypes (M1-­ M5) that are differentially distributed throughout the central nervous system [219]. Since the orthosteric acetylcholine binding site is highly conserved across M1–M5, it has been difficult to develop subtype-selective pharmacological tools for assessing the biological role of individual mAChR subtypes. The discovery of the ­M1/ M4-preferring orthosteric agonist xanomeline and its demonstrated antipsychotic efficacy in a pilot clinical trial with schizophrenia patients were breakthroughs that renewed interest in probing muscarinic mechanisms for the treatment of schizophrenia [220]. However, it was still unclear whether M1 activation, M4 activation, or both were required for conferring antipsychotic efficacy. To achieve the necessary mAChR subtype selectivity, compounds that targeted less conserved regions of the

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M1 or M4 muscarinic receptor, also known as allosteric sites, were identified. In this first example, we will detail the rationale for the drug discovery of M4 positive allosteric modulators (PAMs), i.e., compounds that potentiate the effects of acetylcholine at M4, but have no intrinsic activity alone, for the treatment of the positive symptoms of schizophrenia. Then we will discuss the in vivo assays used to determine efficacy, target validation, and behavior to circuitry mapping for functional target engagement. In situ hybridization studies demonstrated high levels of M4 mRNA expression in brain regions involved in the pathophysiology of schizophrenia such as the nucleus accumbens and striatum but also moderate expression in prefrontal cortical, hippocampal, and thalamic areas [219]. M4 knockout mice exhibit a hyperdopaminergic phenotype with increased basal motor activity and an increased locomotor response to D1, but not D2 dopamine receptor agonists. Likewise, M4 knockout mice displayed an absence of the inhibitory effect of the typical antipsychotic drug haloperidol, a D2 dopamine receptor antagonist suggesting that potentiation of M4 may have antipsychotic activity [221]. High-throughput cell-based screening using Ca2+-mobilization and thallium flux assays followed by chemical library expansion of early hits resulted in the discovery of VU0152100, an M4 PAM with moderate sub-micromolar potency, high selectivity versus M1, M2, M3, and M5, favorable brain bioavailability and in vivo efficacy in reversing amphetamine-induced hyperlocomotion [222]. Subsequently, we established dose-related pharmacodynamic efficacy of VU0152100  in reversing amphetamine-­induced hyperlocomotion (Fig. 3.2) and demonstrated target specificity in this model by the absence of behavioral efficacy in M4 knockout mice [223]. We then examined the relationship between behavioral efficacy and changes in the dopaminergic circuit activity underlying the behavioral readout. Using in  vivo microdialysis and simultaneous recording of behavioral activity, we demonstrated that a dose of VU0152100 that reduced amphetamine-induced hyperlocomotion also reduced elevated extracellular dopamine level in the nucleus accumbens. As the final step, we used pharmacologic magnetic resonance imaging (phMRI) as a translational biomarker of target engagement to evaluate the effects of VU0152100 on amphetamine-induced increases in brain activity across several brain regions. This study demonstrated a brain region-dependent reversal of amphetamine-induced increases in the cerebral blood volume in the nucleus accumbens, dorsal striatum, and other forebrain regions. Taken together, these studies demonstrated that M4 PAMs, as exemplified by VU0152100, warranted further efforts to develop preclinical candidates for subsequent testing of clinical efficacy in schizophrenia patient populations. Ongoing studies at the Warren Center for Neuroscience Drug Discovery in collaboration with Neumora are currently focused on the development of a novel M4 PAM for the treatment of schizophrenia. Fig. 3.2  (continued) Collectively, these data are consistent with an antipsychotic-like profile of VU0152100 and provide preclinical validation for M4 PAMs as a potential mechanism in treating schizophrenia. Abbreviations: AHL amphetamine-induced hyperlocomotion, NA nucleus accumbens, WT wild type, KO knockout, PAM positive allosteric modulator. (This figure is modified from the original publication in Byun et al., Antipsychotic Drug-Like Effects of the Selective M4 Muscarinic Acetylcholine Receptor Positive Allosteric Modulator VU0152100, Neuropsychopharmacology, published 2014 by Springer Nature [223])

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Fig. 3.2 M4-positive allosteric modulator (PAM) VU0152100 as an example of the use of animal models in different stages of drug discovery for development of a novel antipsychotic drug. VU0152100 reversed amphetamine-induced increases in locomotion (AHL), a preclinical model predictive of antipsychotic-like activity. This reversal of AHL was absent in the M4 knockout mice, providing validation that M4 is mediating the observed effects. This behavior can be mapped to circuit level changes in dopamine release, as evaluated by in vivo microdialysis. The doses that produced a reversal of AHL also attenuated amphetamine-induced increases in extracellular dopamine in the NA. Pharmacologic magnetic resonance imaging (phMRI) was used to understand the effects of selective potentiation of M4 on region-specific brain activation of NA in combination with amphetamine. Amphetamine induced a robust increase in cerebral blood volume in brain regions, including the nucleus accumbens, and this activation was reversed by VU0152100.

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3.3.7 Example of In Vivo Characterization of the Selective mGlu5 NAM Basimglurant Through the Late Stage Preclinical Discovery Basimglurant (RG7090, RO4917523; 2-chloro-4-[1-(4-fluoro-phenyl)-2,5-­ dimethyl-­1H-imidazol-4-ylethynyl]-pyridine) is a metabotropic glutamate receptor subtype 5 (mGluR5) negative allosteric modulator (NAM), which recently underwent clinical trials for MDD. Although basimglurant failed in phase II clinical trials due to lack of efficacy, evidence in multiple secondary endpoints suggests that this compound, and more importantly the mGluR5 mechanism, holds promise as a novel treatment for MDD. It also represents an excellent example of the use of animal models throughout the stage of drug discovery for a psychiatric disorder. mGluR5 is an excitatory Gq-coupled GPCR primarily expressed in the cortical and limbic regions associated with the processing of cognition, motivation, and emotion [224]. Subcellularly, it is primarily localized in the postsynaptic density on glutamatergic neurons [225, 226]. Early pharmacological tool compounds used in target validation include MPEP [2-methyl-6-(phenylethynyl)pyridine] [227] and later MTEP (3-[(2-methyl-1,3-thiazol-4-yl)ethynyl]-pyridine) [228], both selective mGluR5 antagonists. These compounds reduced immobility time in the FST, suggesting possible antidepressant-like activity in wildtype mice [229, 230]. Importantly, these effects were absent in the mGluR5 knockout mice, and these mice had lower baseline immobility [230], consistent with a role of mGluR5 in the antidepressant-­like effects seen in this assay. The high-throughput screen performed in basimglurant development was a calcium mobilization assay assessing the function of mGluR5 receptors, using mGluR5 from both humans and rats transfected into HEK293 cells [231]. Pharmacokinetic profiles were assessed in Wistar rats, showing good central nervous system penetrance, a 7.5  h half-life, and 50% oral bioavailability [232]. Later profiling in cynomolgus monkeys showed a longer half-life at 20 h and a similar 50% bioavailability in fed animals, with a fasted bioavailability of 100% [232]. In regards to the in vivo efficacy profile of basimglurant in animal models for MDD, basimglurant was tested in both forced swim and ICSS models as described in section “Major Depressive Disorder”. Using the unpredictable chronic mild stress model to disrupt ICSS motivational behaviors and model anhedonic-like activity, repeated treatment with basimglurant (3 mg/kg) once-daily for 3 weeks normalized the observed anhedonia index of the chronically stressed rats, bringing it back to a pre-stress level [232]. Acute oral basimglurant also significantly reduced immobility in the forced swim test at both 10  mg/kg and 30  mg/kg consistent with antidepressant-­like activity and comparable to the effects observed with MTEP and MPEP [232]. These assays show that basimglurant has efficacy in animal models for different symptoms of MDD. A thorough assessment of functional target engagement and receptor occupancy was also included in the preclinical candidate profiling of basimglurant. Functional MRI was used to examine the dose-related effects of basimglurant on rat brain activity

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patterns. Basimglurant produced robust dose-related changes in rat brain activity patterns within the dose range that also produced antidepressant-like and anti-anhendoniclike activity. In particular, basimglurant increased activity in the dorsal striatum, while it decreased activation of the medial prefrontal cortex, dorsal hippocampus, thalamus, hypothalamus, septum, accumbens, ventral pallidum, and entorhinal piriform cortex [232]. Importantly, when these regional changes in brain activity were compared with the activity of other approved antidepressants (duloxetine, reboxetine, imipramine, and bupropion), the patterns of activity as measured by fMRI were comparable, suggesting that the effects of basimglurant may be similar to other antidepressants. These data also provided a clear dose-related measurement of functional mGluR5 target engagement using fMRI for translational studies in clinical populations. To understand receptor occupancy and brain exposure, [3H]ABP688 [233] (another mGluR5 NAM) and [3H]basimglurant were used for in vivo receptor occupancy studies using Sprague-Dawley rats and C57/Bl6J mice. [3H]ABP688 binding was completely displaced by a 3 mg/kg oral dose of basimglurant [232], with high levels of occupancy observed in the cortex, hippocampus, striatum, amygdala, and nucleus accumbens [232]. These studies also provided a clear measurement of dose-­ related mGluR5 target occupancy that could be adapted using a selective mGluR5 NAM PET ligand like [18F]FPEB for translational PET studies in clinical populations. Insomnia is both a risk factor for and a symptom of depression, making EEG another good biomarker for the effects of antidepressants [234, 235]. In light of this, the effects of basimglurant (0.03–0.3 mg/kg) dosed daily at 2 h into the active cycle for 5 days were examined by recording EEG for 22 h after the last dose. Basimglurant significantly and dose-dependently decreased the REM/non-REM ratio and reduced time spent in REM at the two highest doses within the dose range used in the preclinical models [232]. During non-REM sleep, basimglurant also increased delta power at all doses [232]. Overall, the profile of basimglurant was consistent with wake-promoting effects. These findings also provided a dose-related measurement of functional mGluR5 target engagement using EEG for future translational studies in clinical populations. Unfortunately, despite the extensive preclinical characterization of basimglurant across behavioral, biomarker, and pharmacokinetic domains, when basimglurant was evaluated for potential efficacy in a Phase II clinical trial in patients with treatment-­ resistant MDD, it failed to significantly differ from placebo on the primary outcome measure of the clinician-scored Montgomery-Asberg Depression Rating Scale (MADRS) [236, 237]. There are multiple factors that may have contributed to this failed clinical trial, including the reported high placebo response and the choice of the primary outcome measure and patient population. However, one critical factor was the lack of biomarker studies to determine the dose-related levels of mGluR5 target occupancy and/or functional target engagement achieved in either healthy volunteer subjects or MDD patients, despite the detailed preclinical package that provided a comprehensive understanding of the occupancy-to-efficacy relationships and measures of functional mGluR5 target engagement across the different animal models. Additionally, basimglurant activity was evaluated primarily when given alone in the

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preclinical models, but not when administered in combination with various antidepressant drugs. Yet the clinical evaluation of basimglurant efficacy was conducted as an adjunct therapy to ongoing antidepressant treatments in the patient populations tested [237]. Taken together, these findings suggest that mGluR5 NAMs remain a promising mechanism for the treatment of MMD that awaits further clinical validation. Moreover, the discovery of basimglurant provides an excellent example of the use of animals in the various stages of the psychiatric drug discovery process as well as a demonstration of the importance of using that preclinical data to better inform the clinical trial design (see [238, 239] for more on this topic).

3.4 Future Innovations for Animal Models in Psychiatric Drug Discovery As discussed previously, while there are no perfect animal models for different psychiatric disorders, this does not mean that the current models do not have a place in drug discovery. Instead, it means that researchers in drug discovery are constantly striving to improve currently used animal models, to more closely model different aspects of psychiatric disorders and to ensure that the correct model is being used for the appropriate stage in the discovery process. Using a variety of complementary animal models which account for multidimensional analyses of a psychiatric disorder is a strategy that can improve the applicability of data collected from animal models. For example, when developing a drug for schizophrenia, this means assessing the effects of a compound in models of cognitive, positive, and negative symptoms. In addition, this may mean assessing a potential drug in a variety of genetic models and stratifying patient populations for clinical trials according to those genetic models, such as limiting initial trials and subsequent approval of a drug for patients with a particular genetic risk factor for schizophrenia. Animal models can be used to discover the full scope of contexts where a prospective drug may or may not be useful. With this information, clinical trials can be designed with the primary endpoints most relevant to the specific effects of a drug, rather than including all patients under a given diagnosis. This increased specificity may lead to a decreased overall prospective patient population for a drug but simultaneously more successful clinical trials.

3.4.1 RDoC Framework for Clinical to Preclinical Translational Studies for New Animal Model Development In 2009, the National Institute of Mental Health (NIMH) launched the Research Domain Criteria Initiative (RDoC) to bridge gaps between translational and clinical research and to establish pathophysiological mechanisms underlying mental

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illnesses. The goal of RDoC is to establish a classification system for mental illnesses beyond clinical consensus alone [240]. The RDoC initiative classifies mental illnesses based on the following assumptions: (1) brain circuitry is disrupted in brain disorders, (2) neurocircuitry dysfunctions can be identified using clinical technologies such as fMRI and EEG, and (3) genetics and clinical neuroscience will reveal biosignatures that can be used for diagnosis and treatment [241]. The RDoC framework is a two-dimensional matrix to understand genetics, circuitry and neurobiology, and frame future studies [242]. The matrix compares broad constructs of behavior to units of analysis to identify areas that need to be assessed. This allows for delineation of the genetic, circuitry and neurobiological functions underlying disease-associated behaviors and cognitive functions in psychiatric illnesses. The domains are positive valence systems, negative valence systems, systems for social process, cognitive systems, sensorimotor systems, and arousal/regulatory systems [240]. The measurable units of analysis are genes, molecules, circuits, physiology, paradigm, and self-reports [240]. The intersection of each construct identifies areas of focus to develop studies which will delineate the genetic, circuitry, and neurobiological functions underlying associated behaviors and brain functions in the mental illness. The RDoC framework to assign neurocircuitry and neurobiological mechanisms to psychiatric illnesses directly invites the use of preclinical animal models not only for novel findings, but to translate behaviors and physiological data in human studies. For example, gene variations observed in schizophrenia patients such as copy number variants have been studied in transgenic mouse models to assess the neurocircuitry dysfunctions and behavior associated with copy number variants, reviewed in the following [243]. Animal models for psychiatric illnesses aligned with the RDoC framework provide valid models that can be used in drug discovery.

3.4.2 Novel Technologies Enabling Development of Animal Models Novel Genetic Approaches The clustered regularly interspersed short palindromic repeat/CRISPR-associated nuclease 9 (CRISPR/Cas9) technology provides exciting novel genetic engineering strategies for the development of better animal models of psychiatric diseases. The CRISPR/Cas9 technology targets genes in a sequence specific manner using guide RNA to identify the specific target gene in any location of genomic DNA of any tissue. Once the target is identified, DNA is cut and edited to the guide RNA using nonhomologous end joining (NHEJ) or homology-directed repair (HDR) [244, 245]. CRISPR/Cas9 technology, unlike Cre-recombinase technology previously mentioned, does not require embryonic engineering. CRISPR/Cas9 also can target multiple genes at once and can be delivered directly into brain tissue, increasing its applications across studies in neurodegenerative diseases [244, 245]. A further

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development of this technology is the Cre-driven expression of Cas9 in mouse models which overcomes the challenge of expressing Cas9 in the brain [246]. One exciting application of this novel genetic engineering technology has been the ability to develop genetically modify nonhuman primates with genetic disruptions associated with clinical psychiatric populations for future psychiatric drug development. For example, utilization of CRISPR/Cas9 allowed disruptions of exons 6 and 12 of SHANK3 gene in cynomolgus monkeys [247]. Similar disruptions in the SHANK3 gene, which encodes a scaffolding protein localized in the postsynaptic density of excitatory synapses, have been shown to contribute to the pathogenesis of autism spectrum disorder (ASD) patient cases in Canada [248]. Longitudinal studies over 26 months with one male cynomolgus monkey with a 2 base pair deletion in exon 12 of SHANK3 (SHANK3M3) demonstrated that this genetic monkey model displayed core behavioral phenotypes of ASD, including deficits in social interaction and stereotypical locomotor activity that were improved by treatment with the SSRI fluoxetine [249].  ovel Techniques to Study Neurocircuitry Abnormalities N in Psychiatric Disorders One of the challenges to establishing the connection between psychiatric illnesses and neurocircuitry has been a lack of technologies to regulate and detect signaling in vivo. Optogenetic approaches use light-responsive proteins to probe and induce changes in circuitry. Designer Receptors Exclusively Activated by Designer Drugs (DREADDs) are a chemogenetic technology in neuroscience that takes advantage of GPCR signaling mechanisms to selectively activate specific neural circuits. GCaMP is a fluorescent calcium sensor that takes advantage of intracellular calcium release in neurotransmission. These technologies have enhanced neurocircuitry studies in alignment with the RDoC framework to identify neurocircuitry and neurobiology underlying psychiatric illnesses. Optogenetics and dLight Signaling Strategies Optogenetics is a novel technique that uses light to control biological activities. Opsins are light-sensitive ion channels that induce movement of ions into the intracellular environment [250–252]. Other optogenetic proteins consist of cryptochromes, light-oxygen-voltage receptors, blue-light sensor proteins, and UV-sensitive receptors. These optogenetic proteins probe second messenger interactions, protein-protein interactions, protein activation, and protein inactivation upon absorbing light [253]. Expression of these proteins using gene expression technologies allows for the targeted expression of these proteins in animal models to study the neuronal circuits via light activation. Animal studies using optogenetic technologies have provided the ability to study circuitry, neuronal signaling, and second messenger mechanisms to understand their effects on associated behaviors

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in freely moving mice with high temporal and spatial resolution [254–257]. Optogenetic neurotransmitter sensors have been engineered to emit a fluorescence signal upon activation or binding of the ligand [258, 259]. The dLight1.1 dopamine sensor is an optogenetic dopamine sensor engineered from the D1 receptor fused with a circularly permutated green fluorescent protein which fluoresces when the conformation of the receptor changes after binding dopamine [259]. The advantage of this technology is the ability to detect both tonic and phasic dopamine signaling in response to various stimuli. The application of this technology then allows researchers to directly study dopamine signaling in response to biological, pharmacological, and environmental conditions under normal conditions and in psychiatric disease models. D-light technology also allows for the detection of changes in dopamine signaling evoked by optogenetic manipulations [259]. This novel application was used to differentiate neuronal firing events in the neurons of the VTA from signaling events on postsynaptic neurons in the nucleus accumbens (NAc), which are important for reward perception [260]. These studies revealed that VTA neuronal firing does not cause dopamine release in the NAc in response to reward perception, a critical mechanism involved in motivation and drug-seeking behaviors in psychiatric populations. DREADDs Designer receptors exclusively activated by designer drug (DREADD)-based chemogenetic tools are designed to identify underlying circuitry associated with psychiatric disorders [261, 262]. This technology, based on GPCR signaling mechanisms, relies on the conditional genetic expression of the DREADD receptor and the administration of the designer drug to activate the receptor mechanisms. The human M3 muscarinic DREADD receptor coupled to Gq (hM3Dq),  activated specifically by bioavailable clozapine-N-oxide (CNO), is widely used to activate neuronal firing [263]. The human M4 muscarinic DREADD receptor coupled to Gi (hM4Di) is used to attenuate neuronal firing also upon activation with CNO [263, 264]. DREADD studies in transgenic mouse models have demonstrated inducible-­ conditional expression and subsequent behavioral and electrophysiological effects upon administration of CNO, the associated designer drugs [264]. Advantages to this approach in comparison to optogenetic approaches are that the activation of DREADDs is noninvasive and does not rely on the availability of a light source or other technology. Limitations to the technology involve complexities with CNO kinetics in animal models and appropriate coupling of G-proteins within the various signaling pathways. One application of this technology for understanding the neural circuitry underlying symptoms of anxiety has demonstrated that chronic activation of the hM3Dq DREADD using CNO in the excitatory forebrain neurons of mice during a critical postnatal period enhances anxiogenic-like behaviors in later development and long-term alterations in metabolic rate of glucose oxidation in the hippocampal and cortical brain regions [265].

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GCaMP In vivo calcium imaging represents an exciting direct readout of neuronal activity in animal model for psychiatric disorders. GCaMPs are members of a larger family of genetically encoded calcium indicators (GECIs) [266]. GCaMPs contain a circularly permutated green fluorescent protein, calmodulin (CaM), and muscle myosin light chain kinase (M13) [267, 268]. Calcium binding to GCaMPs changes fluorescence intensity. Similar to optogenetics, fiber optic recordings are required to obtain data for in vivo GCaMP calcium recordings [269–270]. GCaMP signaling technology can also serve as a reverse translational technology to measure neuronal activity compared to fMRI studies in human studies. For example, GCaMP6 conditionally expressed in excitatory neurons has been used to study signaling in healthy animals and in animals with experimentally induced strokes [271]. Changes in GCaMP in excitatory neurons in mice after stroke induction were shown to be consistent with cortical alterations detected by fMRI analysis in human stroke patients [271]. This study demonstrates the promising translational capacity of in vivo calcium imaging using GCaMP technology. Novel High-Throughput Behavioral Screening Technologies Behavioral phenotyping is an essential element of drug discovery for psychiatric diseases. As previously discussed, discrete behavioral assays can be used to test the acute or chronic effects of different psychiatric drugs and potential underlying mechanisms related to the associated behaviors. However, such rodent models have limited throughput. More recently, behavioral phenomics has emerged as data driven approaches to integrate automated testing systems with bioinformatics [272, 273]. The PsychoGenics smartcube is one such in  vivo high-throughput testing platform that collects over half a million data points during each automated testing session, then uses bioinformatic analysis to translate these data into over 2000 different behavioral features in order to create behavioral drug signatures. It also allows for both acute and chronic monitoring of psychiatric drug effects on different social, circadian, and cognitive behaviors in mice. Successful application of this in  vivo high-throughput technology to conduct a behavior-driven screen with chemically diverse compound libraries provided through a collaboration with Sunovion Pharmaceuticals, resulted in the identification of SEP-363856, a novel trace amine receptor 1 (TAAR1) agonist with serotonin 5-HT1A activity, with demonstrated statistically and clinically meaningful improvements in the Positive and Negative Symptom Scale (PANSS) of schizophrenia [274, 275].

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3.5 Summary and Future of Animal Models in Psychiatric Drug Discovery In conclusion, ongoing advances in genetic, neural circuitry-based, and automated behavioral technologies combined with the application of the RDoC platform are leading to exciting innovations in the modeling of the underlying circuitry and biologic abnormalities associated with various psychiatric disorders. These innovations represent great potential for expanding the utility and reliability of animal models for the discovery and development of NCEs for psychiatric disorders.

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342. Karayiorgou M, Morris MA, Morrow B, Shprintzen RJ, Goldberg R, Borrow J, et  al. Schizophrenia susceptibility associated with interstitial deletions of chromosome 22q11. Proc Natl Acad Sci U S A. 1995;92:7612–6. 343. Xu B, Roos JL, Levy S, Van Rensburg EJ, Gogos JA, Karayiorgou M. Strong association of de novo copy number mutations with sporadic schizophrenia. Nat Genet. 2008;40:880–5. 344. Campbell LE, Daly E, Toal F, Stevens A, Azuma R, Catani M, et al. Brain and behaviour in children with 22q11.2 deletion syndrome: a volumetric and voxel-based morphometry MRI study. Brain. 2006;129:1218–28. 345. Simon TJ, Bish JP, Bearden CE, Ding L, Ferrante S, Nguyen V, et al. A multilevel analysis of cognitive dysfunction and psychopathology associated with chromosome 22q11.2 deletion syndrome in children. Dev Psychopathol. 2005;17:753–84. 346. Gothelf D, Law AJ, Frisch A, Chen J, Zarchi O, Michaelovsky E, et al. Biological effects of COMT haplotypes and psychosis risk in 22q11.2 deletion syndrome. Biol Psychiatry. 2014;75:406–13. 347. Didriksen M, Fejgin K, Nilsson SRO, Birknow MR, Grayton HM, Larsen PH, et al. Persistent gating deficit and increased sensitivity to NMDA receptor antagonism after puberty in a new mouse model of the human 22q11.2 microdeletion syndrome: a study in male mice. J Psychiatry Neurosci. 2017;42:48–58. 348. Tripathi A, Spedding M, Schenker E, Didriksen M, Cressant A, Jay TM.  Cognition- and circuit-based dysfunction in a mouse model of 22q11.2 microdeletion syndrome: effects of stress. Transl Psychiatry. 2020;10:1–15. 349. Hodgkinson CA, Goldman D, Jaeger J, Persaud S, Kane JM, Lipsky RH, et al. Disrupted in schizophrenia 1 (DISC1): association with schizophrenia, schizoaffective disorder, and bipolar disorder. Am J Hum Genet. 2004;75:862–72. 350. Kamiya A, Kubo KI, Tomoda T, Takaki M, Youn R, Ozeki Y, et al. A schizophrenia-associated mutation of DISC1 perturbs cerebral cortex development. Nat Cell Biol. 2005;7:1067–78. 351. Niwa M, Kamiya A, Murai R, Kubo K, Gruber AJ, Tomita K, et al. Knockdown of DISC1 by in utero gene transfer disturbs postnatal dopaminergic maturation in the frontal cortex and leads to adult behavioral deficits. Neuron. 2010;65:480–9. 352. Andersen MP, Pouzet B.  Effects of acute versus chronic treatment with typical or atypical antipsychotics on d-amphetamine-induced sensorimotor gating deficits in rats. Psychopharmacology. 2001;156:291–304. 353. Mavrikaki M, Nomikos GG, Panagis G. Efficacy of the atypical antipsychotic aripiprazole in d-amphetamine-based preclinical models of mania. Int J Neuropsychopharmacol. 2010;13:541–8. 354. Kitaichi K, Yamada K, Hasegawa T, Nabeshima T, Furukawa H.  Effects of risperidone on phencyclidine-induced behaviors: comparison with haloperidol and ritanserin. Jpn J Pharmacol. 1994;66:181–9. 355. Hoffman DC. Typical and atypical neuroleptics antagonize MK-801-induced locomotion and stereotypy in rats. J Neural Transm Gen Sect. 1992;89:1–10. 356. Minnaard AM, Ramakers GMJ, Vanderschuren LJMJ, Lesscher HMB.  Baclofen and naltrexone, but not N-acetylcysteine, affect voluntary alcohol drinking in rats regardless of individual levels of alcohol intake. Behav Pharmacol. 2021;32:251–7. 357. Mello NK, Negus SS. Preclinical evaluation of pharmacotherapies for treatment of cocaine and opioid abuse using drug self-administration procedures. Neuropsychopharmacology. 1996;14:375. 358. Weeks JR. Experimental morphine addiction: method for automatic intravenous injections in unrestrained rats. Science. 1979;1962(138):143–4. 359. Leri F, Tremblay A, Sorge RE, Stewart J.  Methadone maintenance reduces heroin- and cocaine-induced relapse without affecting stress-induced relapse in a rodent model of poly-­ drug use. Neuropsychopharmacology. 2004;29:1312–20. 360. Mello NK, Mendelson JH, Bree MP, Lukas SE.  Buprenorphine and naltrexone effects on cocaine self-administration by rhesus monkeys. J Pharmacol Exp Ther. 1990;254:926–39.

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361. Mello NK, Lukas SE, Mendelson JH, Drieze J.  Naltrexone–buprenorphine interactions: effects on cocaine self-administration. Neuropsychopharmacology. 1993;9:211–24. 362. Jordan CJ, Cao J, Newman AH, Xi ZX. Progress in agonist therapy for substance use disorders: lessons learned from methadone and buprenorphine. Neuropharmacology. 2019;158:107609. 363. Beach HD. Morphine addiction in rats. Can J Psychol. 1957;11:104–12. 364. Bespalov AY, Tokarz ME, Bowen SE, Balster RL, Bear. Effects of test conditions on the outcome of place conditioning with morphine and naltrexone in mice. Psychopharmacology. 1999;141:118–22. 365. Houj M, Bisaga A, Popik P. Conditioned rewarding effects of morphine and methadone in mice pre-exposed to cocaine. Pharmacol Rep. 2013;65:1176–84. 366. Myers MM, Musty RE, Hendley ED.  Attenuation of hyperactivity in the spontaneously hypertensive rat by amphetamine. Behav Neural Biol. 1982;34:42–54. 367. Sagvolden T. The alpha-2A adrenoceptor agonist guanfacine improves sustained attention and reduces overactivity and impulsiveness in an animal model of attention-deficit/hyperactivity disorder (ADHD). Behav Brain Funct. 2006;2:41. 368. Miller EM, Pomerleau F, Huettl P, Russell VA, Gerhardt GA, Glaser PEA. The spontaneously hypertensive and Wistar Kyoto rat models of ADHD exhibit sub-regional differences in dopamine release and uptake in the striatum and nucleus accumbens. Neuropharmacology. 2012;63:1327–34. 369. Zhuang X, Oosting RS, Jones SR, Gainetdinov RR, Miller GW, Caron MG, et al. Hyperactivity and impaired response habituation in hyperdopaminergic mice. Proc Natl Acad Sci U S A. 2001;98:1982–7. 370. Hardung S, Jäckel Z, Diester I. Prefrontal contributions to action control in rodents. Int Rev Neurobiol. 2021;158:373–93. 371. Moon SJ, Kim CJ, Lee YJ, Hong M, Han J, Bahn GH. Effect of atomoxetine on hyperactivity in an animal model of attention-deficit/hyperactivity disorder (ADHD). PLoS One. 2014;9:e108918.

Chapter 4

Discovery and Development of Monoamine Transporter Ligands Shaili Aggarwal and Ole Valente Mortensen

Abstract  Monoamine transporters (MATs) are targets of a wide range of compounds that have been developed as therapeutic treatments for various neuropsychiatric and neurodegenerative disorders such as depression, ADHD, neuropathic pain, anxiety disorders, stimulant use disorders, epilepsy, and Parkinson’s disease. The MAT family is comprised of three main members – the dopamine transporter (DAT), the norepinephrine transporter (NET), and the serotonin transporter (SERT). These transporters are through reuptake responsible for the clearance of their respective monoamine substrates from the extracellular space. The determination of X-ray crystal structures of MATs and their homologues bound with various substrates and ligands has resulted in a surge of structure-function-based studies of MATs to understand the molecular basis of transport function and the mechanism of various ligands that ultimately result in their behavioral effects. This review focusses on recent examples of ligand-based structure-activity relationship studies trying to overcome some of the challenges associated with previously developed MAT inhibitors. These studies have led to the discovery of unique and novel structurally diverse MAT ligands including allosteric modulators. These novel molecular scaffolds serve as leads for designing more effective therapeutic interventions by modulating the activities of MATs and ultimately their associated neurotransmission and behavioral effects. Keywords  Dopamine · Serotonin · Norepinephrine · Antidepressants · Psychostimulants · Allosteric modulators

S. Aggarwal (*) · O. V. Mortensen (*) Department of Pharmacology and Physiology, Drexel University College of Medicine, Philadelphia, PA, USA e-mail: [email protected]; [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 M. Macaluso et al. (eds.), Drug Development in Psychiatry, Advances in Neurobiology 30, https://doi.org/10.1007/978-3-031-21054-9_4

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4.1 Introduction and Overview of Monoamine Transporters The monoamine neurotransmitter transporters (MATs) are part of the solute carrier 6 (SLC6) family of transporters [1, 2] and are namely the dopamine transporter (DAT, SLC6A3), the norepinephrine transporter (NET, SLC6A2), and the serotonin transporter (SERT, SLC6A4) which mediate the reuptake of monoamine neurotransmitters dopamine (DA), norepinephrine (NE), and serotonin (5-HT), respectively, from the extracellular space into the intracellular presynaptic compartment. The MATs are membrane-bound transporters expressed in presynaptic neuronal terminals of their respective pathways within the CNS and mediate a rapid reuptake of neurotransmitters from the synaptic cleft into the presynaptic neurons, where the neurotransmitters are sequestered into synaptic vesicles (via vesicular monoamine transporters or VMAT) for recycling and release or are degraded by monoamine oxidase enzymes. The transport of substrates by the transporters is favored by the energy gradient produced by the movement of Na+ ions into the cell and therefore driven by the concentration gradient created by Na+/K+ ATPase. DAT and NET transport one dopamine or norepinephrine molecule along with 2 Na+ ions and one Cl− ion, whereas SERT cotransports one 5-HT molecule with one Na+ and one Cl− along with the counter-transport of one K+. Thus, the MATs are sometimes also referred to as Na+/ Cl−-symporters [3].

4.2 Therapeutic Relevance of MATs Since MATs control the signal amplitude and duration of monoaminergic neurotransmission, they remain a prominent therapeutic target of interest for the treatment of several neurological disorders [4]. In addition, the MATs are also the primary targets of action of a number of psychostimulants and recreational drugs of abuse such as cocaine, methamphetamine, 3,4-methylenedioxy-methamphetamine (“ecstasy” or MDMA), cathinones (or “bath salts”) which all either block or reverse the transport of neurotransmitters and as a result increase the synaptic neurotransmission leading to stimulatory effects. Tricyclic antidepressants (e.g., clomipramine and amitriptyline) and the selective inhibitors of SERT (also known as selective serotonin-reuptake inhibitors or SSRIs) such as fluoxetine, sertraline and paroxetine are commonly prescribed for depression, anxiety, and panic disorders. Bupropion, a DAT inhibitor, is an antidepressant and smoking cessation aid. Methylphenidate, another DAT-inhibitor is marketed for attention-deficit hyperactivity disorder (ADHD). Reboxetine is used in depression, panic disorder, and ADHD. Different from targeting the inhibition of MATs for use in mood- or cognition-related disorders, synthetic compounds that act as non-­ selective substrates of MATs and promote monoamine efflux have also found application for clinical use. For example, mixed amphetamine salts (racemic mixture of amphetamine isomers) are prescribed in low doses to treat ADHD and are commonly used off-label to improve cognition and to help in narcolepsy by promoting

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wakefulness. However, such drugs along with many other cognition-enhancing drugs that interact with MATs are strictly controlled and regulated because of their abuse liability.

4.3 Structural Insights and Transport Mechanism Breakthrough discoveries such as crystal structures of homologous bacterial (Aquifex aeolicus) leucine transporter (LeuT) [5–7], Drosophila melanogaster dopamine transporter (dDAT) [8–10] and human serotonin transporter (hSERT) [11] have been pivotal in enhancing our understanding of the structural biology of the MATs and in guiding further studies to elucidate underlying molecular mechanisms of ligand transport and interaction. The X-ray crystal structure of the bacterial leucine transporter (LeuT) from Aquifex aeolicus that shares 20–25% overall homology with the MATs [6] gave insights into the tertiary arrangement of the transporters and their functioning, especially of the core region which shares ~60% homology with the MATs. The co-­ crystal structures of Drosophila melanogaster DAT (dDAT) bound to the substrate DA, D-amphetamine, methamphetamine, cocaine, and many other ligands which has 50–55% homology with the human MATs [8–10] and the human SERT in complex with paroxetine and escitalopram [11–13] further enhanced our understanding of mechanism of transport and ligand induced structural conformations of MATs. The structure of all MATs is comprised of 12 alpha-helical transmembrane spanning domains connected with flexible intracellular and extracellular loops. The Nand C-termini lie in the intracellular region. The high affinity primary substrate binding site, also referred to as the S1 or orthosteric site, lies at the core of the translocation pathway located between TM1 and TM6. The S1 site holds a substrate molecule along with one or two Na+ ions. The S1 pocket is comprised of a hydrophobic region, which holds the aromatic substituents of the substrates, and a hydrophilic or a polar region that contains a conserved aspartate residue (SERT: D98, DAT: D79, NET: D75) to form ionic interactions with the amine group of the substrates. The transporters translocate the substrate via a three-state “alternating access” mechanism through sequential binding and conformational changes [1]. According to the “alternating access” mechanism, the transporter adopts distinct conformations where the access to the central binding site is alternatingly sealed from the extracellular and the intracellular side facilitated by the opening and closing of the gating networks present above and below the S1 site. The substrate and the ions bind to the transporter when it adopts an outward-open conformation, which further triggers the closing of the transporter, and thereby occluding the substrate and the ions from either side of the membrane. Next, the occluded state is followed by the opening of the intracellular gate, leading to an inward-facing conformation, which releases the ions and substrate into the cytoplasm via diffusion facilitated by hydration of the substrate binding site. The recently reported SERT cryo-EM structure in complex with ibogaine provided further insights into the

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s­ tructural rearrangements that occur during the translocation cycle. Ibogaine is a hallucinogenic natural product with psychoactive and anti-addictive properties and a non-competitive inhibitor of transport. It is bound within the S1 site of SERT and the complexes were captured in outward-open, occluded, and inward-open conformations providing a snapshot of the neurotransmitter transport mechanism and inhibition [14].

4.4 Central Binding Site Versus Allosteric Binding Sites in MATs LeuT crystal structures bound with leucine and tryptophan substrates within the S1 site are known in the literature. There are several known co-crystal structures of dDAT (shares 55% homology with human DAT at the amino acid level) in complex with dopamine, amphetamine, cocaine, tricyclic antidepressants, and several other inhibitors bound within the S1 site [10]. In addition, several crystal structures of LeuBAT (LeuT with key residues in the central binding site mutated to corresponding amino acids of human SERT) have been published with mazindol, TCAs, SSRIs, SNRIs, etc., all occupying the S1 site [15]. SERT crystal structures have recently been reported bound to the antidepressants sertraline, fluvoxamine, and paroxetine [12] occupying the central S1 site. Moreover, several homology models and computational studies, that have employed the known crystal structures as templates, have aided in the discovery and development of MAT ligands. Many novel MAT ligands have been identified as promising lead compounds through virtual screening studies using the computational models of MATs. Xue and colleagues [16] provide a comprehensive list of reported computational models known to date. Together, these structures have provided detailed insights into the molecular and structural details of the MAT central binding sites and have led to the advancement in the study of transporter interactions with their ligands and of structural differences among DAT, SERT, and NET [17]. Increasing structural and biochemical evidence have indicated the presence of additional ligand binding sites within the MATs other than the S1 central binding site. These sites most likely are present in the extracellular vestibular region of the transport channel above the S1 site. Several studies in the literature have endeavored to determine the exact molecular and structural features of ligand binding to this region of the transporters. One of the earliest evidences indicating the presence of ligand binding site in the extracellular region comes from the X-ray crystal structures of bacterial transporter LeuT in complex with several TCAs and SSRIs bound in the putative secondary binding site region [5–7, 18, 19]. More recently, hSERT crystal structure with two (S)-citalopram molecules simultaneously bound (one in the S1 site and the other in the extracellular vestibule region) [11] as well as the drastic increase in affinity of some bivalent ligands of SERT and DAT [20] compared to the common

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monovalent ligands strongly indicate the p­ resence of distinct low-affinity ligand binding sites in the extracellular region within MATs other than the high-affinity primary binding site (i.e., S1). These results add to the earlier data on antagonist dissociation experiments of SERT that showed that there is a low-affinity allosteric site in SERT that slows the dissociation of inhibitors from a separate high-affinity site [21]. In this study, it was shown that S-citalopram or clomipramine impeded the dissociation of [3H]-citalopram, although with a relatively low potency of ~5 μM while it is known to bind to the central binding site with high potency. Later, Plenge et  al. used simulations to show that ligand binding in the S1 propagates conformational changes in the S2 site. Recently, the same group reported cryo-EM structure of SERT bound with the antidepressant vilazodone in the extracellular vestibular [22]. In another study, molecular dynamics simulations and comparative genomics techniques identified another allosteric pocket [23, 24] in the extracellular vestibule of SERT and a virtual screening of a database against this site identified a few low potency ligands that specifically modulate the function of SERT ligands known to bind to the high-affinity S1 site. We employed a similar method of hybrid-based pharmacophore approach and virtual screening to identify a novel allosteric binding pocket within the extracellular region of DAT and discovered a screening hit, KM822, which modulates the activity of DAT in beneficial ways [25]. Thus, in addition to the primary binding site S1 observed in the crystal structures of LeuT and SERT, there is a possibility that multiple low affinity binding sites are present in regions distinct from the direct translocation pathway that could serve as allosteric sites for modulating conformational changes in the transporter and affect its function. The relevance of these allosteric sites as functional binding sites for monoamine substrates during translocation and for modulators is a topic of great interest currently.

4.5 Medicinal Chemistry of MAT Ligands A wide range of MAT-interacting compounds have been developed to date as pharmacological and therapeutic tools to modulate and regulate neurotransmission. Different classes of non-selective or selective drugs that can inhibit, modulate, or promote the activity of the three transporters have been extensively developed via design and synthesis efforts to evaluate their efficacy in the treatment of many CNS-­ related diseases such as depression and the abuse of psychostimulants like cocaine and amphetamines. The following provides an overview of structural details of the most prominent ligands of MATs and summarizes the recent medicinal chemistry and structure-activity relationship studies of some of the MAT ligands that have been deemed “unique” and novel in terms of their mode of mechanism, site of action, neurochemical properties, and/or their behavioral effects.

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4.5.1 Structure-Activity Relationship Studies of DAT Ligands Cocaine (1, Fig. 4.1) is a highly addictive drug of abuse which binds to DAT and inhibits the reuptake of dopamine from the synapse into presynaptic neurons. This results in an increase in extracellular dopamine levels which is the primary mechanism of cocaine’s psychostimulant effects and abuse liability. Structurally, cocaine belongs to the tropane alkaloid class of drugs [26] and nonspecifically binds to DAT, NET, and SERT with similar potencies. Numerous substituted derivatives of cocaine with DAT selectivity have been evaluated as potential pharmacotherapies for psychostimulant abuse and other DAT-related disorders. In addition, SAR studies on cocaine have been of interest for many years to characterize the binding sites of cocaine and identify the potency and selectivity requirements of moieties within cocaine for its interaction with DAT. Carroll et al. reported several cocaine analogs through systematic structure activity relationship on cocaine’s structure [27, 28]. The 3-aryl analogues of cocaine were among the first series that provided highly potent and selective compounds against DAT. The position and type of substituents on the 3-aryl ring further improved the affinity and selectivity of these tropanes. WIN-35428 (1a, Fig. 4.1) emerged from the 3-phenyltropanes series with higher affinity and selectivity for DAT over NET and SERT as compared to cocaine. Although this series was explored to find analogs that could block the psychostimulant effects of cocaine by specifically binding to DAT and be useful as anti-addiction therapeutics, most of the analogs produced cocaine-like behavioral effects in animals. Nevertheless, WIN-35428 is extensively used to date as a pharmacological

Fig. 4.1  Chemical structures of DAT inhibitors

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tool in DAT-binding assays and comparative studies as the removal of the phenyl ester group in cocaine’s structure imparted stability in aqueous solutions. RTI-55 (1b) is another compound in this series which has selectivity for DAT and SERT over NET and is commonly used as a reference tool in pharmacological assays. Based on such results, it was hypothesized that cocaine analogs that inhibit DAT to block dopamine transport will have reinforcing effects similar to that of cocaine [29]. However, GBR 12909 (2), a piperazine-based selective DA uptake inhibitor which was in clinical evaluation for cocaine abuse, piqued interest in further discovery of compounds with a desirable behavioral profile [30, 31]. One of the most pivotal discoveries among the tropane class of DAT inhibitors was the compound benztropine (3), with a diphenylether substitution, similar to GBR 12909, at the 3α position and a lack of substituent at the 2-position. Interestingly, benztropine has high affinity and selectivity for DAT, but displayed “atypical” effects where it did not share cocaine’s stimulatory behavioral profile in animal models [32]. Although benztropine was a potent DAT ligand, its binding towards off-target sites confounded the interpretation of its behavioral effects in animal models of addiction. Further exploration of benztropine SAR studies to mitigate the off-target activity showed that the addition of halogen groups at 3- and 4-position of the phenyl rings and modification of the N-Methyl moiety could improve DAT affinity and selectivity of the benztropine analogs and minimize offtarget engagement (Table 4.1) [33]. These efforts led to the discovery of JHW007 (3f), a potent and selective DAT inhibitor with a unique in vivo profile. JHW007, although inhibiting DAT with similar potency as cocaine, did not show cocaine-like stimulant or subjective effects. In addition, JHW007 is also shown to antagonize the behavioral effects of cocaine or methamphetamine [34–36]. Although JHW007 has never been evaluated clinically, benztropine did not produce a desirable response to acute cocaine administration in a clinical setting. Because of the desirable behavioral effects in the animal models, atypical DAT inhibitors have continued to be actively pursued and investigated to elucidate their Table 4.1  Binding data of tropane-based analogs at DAT, NET, and SERT Compound 1, cocaine 1a, WIN35428 1b, RTI-55 2, GBR12935 3, benztropine 3a 3b 3c 3d 3e 3f, JHW007 4, methylphenidate

DAT (Ki, nM) 187 ± 18.7 11 1.26 12.0 ± 1.9 118 ± 18.7 36.8 ± 3.3 26.2 ± 2.1 11.2 ± 1.2 11.8 ± 1.3 399 ± 27.9 24.6 ± 2.0 60 ± 0.01

NET (Ki, nM) 3300 ± 170 NA NA 497 ± 17.0 1390 ± 134 1010 ± 116 508 ± 70.0 NA 610 ± 81 7660 ± 1240 1730 ± 232 100 ± 0.01

SERT (Ki, nM) 172 ± 15 160 4.21 105 ± 11.4 >10,000 1320 ± 194 2100 ± 285 NA 3260 ± 110 3610 ± 214 1330 ± 151 132.43 ± 10.71

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mechanism and find their potential use as psychostimulant abuse medications. Their unique effects are suggestive of a different mode of action indicating a ligand-­ specific control of DAT function. Structure-function studies of typical and atypical DAT ligands have hypothesized that DAT ligands prefer different DAT conformations which subsequently dictate their behavioral effects. Continued efforts in the discovery of atypical ligands have shifted focus to a new generation of atypical DAT ligands comprised of modafinil and its analogs. Modafinil (5, Table 4.2), which is used as a wake-promoting agent for the treatment of narcolepsy and other sleep disorders [37], also has low affinity for DAT and low abuse potential according to the available clinical data [38, 39]. To discover modafinil analogs with improved pharmacological and behavioral profiles that could potentially be developed into addiction therapeutics [40], several SAR studies have been reported. Although modafinil is available as a racemic mixture, studies have suggested that R-(−)modafinil is more metabolically stable, longer-acting than the (S)-enantiomer [41] and slightly more potent (threefold) than the S-(+) counterpart. In addition, although the racemic, R-, and S-enantiomers all stimulated locomotor activity in mice, they were much less effective and less potent than cocaine [37]. Nevertheless, in clinical trials, modafinil has demonstrated limited effectiveness in treating cocaine abuse, although there is some evidence of benefit in nonalcohol-dependent cocaine abusers [42]. Several attempts have been made to further increase the therapeutic efficacy for stimulant use disorders by the design, synthesis, and evaluation of several modafinil analogs to improve its water solubility and DAT affinity.

In one of the earlier SARs explorations of modafinil, it was found that reducing the sulfoxide with sulfide decreased DAT affinity and improved SERT binding if the diphenyl rings are unsubstituted (see Table 4.2) [43]. Addition of alkyl groups on terminal amide nitrogen reduced DAT affinity. Binding affinity at DAT increased with halogen substitutions at para position of the aryl rings in the order of Br > Cl > F ≥ H. In addition, this halogen substitution order was also followed by halogens at meta-positions of the diphenyl rings [43]. Compound 5e displayed remarkable selectivity towards DAT as compared to SERT and NET with 3,3′-di-Cl substitution with thioacetamide scaffold. 4,4′-dimethyl substitution on the diphenyl rings (5k) decreased DAT affinity by fivefold but did not affect the DAT selectivity of the compound. For those analogues that contained unsubstituted diphenyl rings, it was generally observed that for the thioethanamine scaffold, DAT affinity increased with more bulky substituents on terminal amine nitrogen whereas in thioacetamides, DAT affinity decreased with an increase in bulk at the terminal amine

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Table 4.2  Binding affinities of Modafinil and its analogs against DAT, NET, and SERT Compound X 5, H modafinil

Y R S=O H

5a

H

S

5b

H

S=O Methyl

5c

3,3′-di-­ S=O H F

5d

3,3′-di-­ S=O H Cl H 3,3′-di-­ S Cl

5e

H

DAT Z (Ki, nM) C=O 2600 [2430– 2780] C=O 12400 [10800– 14300] C=O 13100 [12600– 13700] C=O 5930 [4990– 7060] C=O 881 [763–1020] C=O 275 [257–295]

NET (Ki, nM) NA

SERT (Ki, nM) NA

NA

NA

NA

NA

NA

NA

NA

NA

45400 [39600– 52000] 11000 [9540– 12600] 9770 [9170– 10400] NA

NA

7090 [6990– 8180] 25500 [23300– 28000] NA

221 [191–257] 10000 [9570– 10400] 5700 [5040– 6440] 927 [786–1090]

5f

4′,4″-di-­ S Br

Methyl

5g

4′,4″-di-­ S Cl

Methyl

5h

H

S

n-butyl

5i

4′,4″-di-­ S Br

n-butyl

5j

4′,4″-di-­ S F

n-butyl

7580 [7210– 7970] 56100 [53900– 58500] NA

980 [938–1020] 17300 [15400– 19400] 11500 [10700– 12300] 5500 [5140– 5880]

5k

5l 5m

C=O 3010 [2770– 3260] C=O 4130 [3620– 4710] C=O 23600 [20500– 27100] C=O 722 [659–792]

C=O 6400 [5820– 7050] 4′,4″-di-­ S=O H C=O 12700 [12400– CH3 13100] H S H CH2 142 [131–155] H S Cyclopropylmethyl CH2 435 [406–466]

5n

H

S

n-butyl

CH2

310 [275–350]

5o

H

S

3-phenylpropyl

CH2

295 [268–325]

5720 [5320– 6150] 10700 [7310– 15700] NA

(continued)

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Table 4.2 (continued) Compound X Y 5p 4′,4″-di-­ S (JJC8-016) F

R 3-phenylpropyl

DAT Z (Ki, nM) CH2 114 [97.4–132]

NET (Ki, nM) 3850 [3830– 3870]

SERT (Ki, nM) 354 [312–402]

Table 4.3  Binding affinities of piperazine-based modafinil analogs Compound X 5q H 5r 4,4′diF 5s 4,4′diF 5t 3,3′diCl 5u H 5v 4,4′(JJC8-091) diF 5w 4,4′(JJC8-088) diF

DAT Y Z R (Ki, nM) S=O C=O 3-phenylpropyl 33.0 ± 2.83 S=O C=O 3-phenylpropane 37.6 ± 1.86

SERT NET (Ki, nM) (Ki, nM) 54300 ± 3210 15200 ± 1100 12000 ± 1430 1320 ± 152

S=O C=O 2-OH-propyl

752 ± 87.4

NA

32800 ± 4430

S=O C=O 2-OH-propyl

1380 ± 191

>50 uM

NA

S S

C C

2-OH-propyl 2-OH-propyl

49.6 ± 4.31 16.7 ± 1.22

44500 ± 2400 26700 ± 2630 17800 ± 885 1770 ± 234

S

C

2-OH, 3-phenylpropyl

6.72 ± 0.977 1950 ± 227

213 ± 13.2

nitrogen [43]. Compound 5l with the thioethanamine scaffold and unsubstituted diphenyl rings was one of the most potent compound towards DAT, however, lost significant DAT selectivity. This indicated that the replacement of amide with amine to increase water solubility was well tolerated. The affinity of compound 5o, with N-propylphenylamine substituent, for DAT increased by tenfold as compared to modafinil and was found to be more selective towards DAT than NET and SERT [41]. The DAT affinity further increased 2.5-fold with 4,4′-difluoro substituted diphenyl-moiety (5p, JJC8-016). In addition, N-cyclopropylmethyl and N-n-butyl substituted analogs (compounds 5m and 5n) were also among the most DAT-­ selective compounds in this series. Further functionalization of the terminal nitrogen was attempted by incorporating the piperazine ring in the main scaffold (Table 4.3) [42].

Compound 5q with a piperazine amide substitution retaining the 3-phenylpropyl moiety of compound 5p displayed 100-fold higher potency than modafinil and high selectivity for DAT as compared to SERT and NET, with additional 4,4′-diF groups

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imparting a modest change in affinity (5r). This series was further diversified by hydroxylating the N-bearing propyl chain. Compounds 5s and 5t with 2-OH-propyl side chain lost potency for DAT but retained high DAT selectivity and were almost inactive at SERT and NET. The removal of amide carbonyl C=O to get compounds like 5u and 5v was well tolerated as well [42]. Comparison of compounds 2-­hydroxypropyl 5v (JJC8-091) and 2-hydroxyphenylpropyl 5w (JJC8-088) revealed that phenyl moiety imparted greater affinity to the compound with DAT affinity threefold higher for 5w than 5v with similar selectivity profile for DAT versus SERT. Compounds JJC8-016, JJC8-088, and JJC8-091 emerged as the most promising compounds with superior DAT affinity compared to modafinil and better aqueous solubility [44]. These compounds were evaluated for their effects on the neurochemistry via brain microdialysis and fast-scan cyclic voltammetry and behavior through ambulatory activity of male Swiss-Webster mice. The results of these studies are summarized in the literature [44–46]. Briefly, compound JJC8-016 reduced the psychostimulant effects in various animal models of addiction. For example, cocaine enhanced locomotion, cocaine self-administration, and cocaine-­ induced reinstatement of drug seeking behavior were dose-dependently reduced by JJC8-016 pretreatment [47] although there is evidence that it might possess cardiotoxic adverse effects similar to that seen with its analog, GBR12909 [48]. Compound JJC8-088 displayed cocaine-like effects and preferred open DAT conformation similar to that of cocaine. Compound JJC8-091 showed promising results in behavioral testing in a murine locomotor assay where it was effective in reducing stimulant effects in rats exposed to long-access (6 h) methamphetamine [48, 49]. Furthermore, JJC8-091 reduced cocaine self-administration and cocaine-primed reinstatement of cocaine seeking [49]. Hence, JJC8-091 emerged as a promising lead compound and structural modifications of this scaffold continue to be reported that have better profile in behavioral models of cocaine abuse and are more metabolically stable [50]. Giancola and colleagues have recently reported a new series of modafinil where they have replaced the metabolically susceptible piperazine ring of compounds like JJC8-016, JJC8-088, and JJC8-091 with more stable bioisosteric moieties aminopiperidine and piperidine amine (Table 4.4). The importance of the tertiary amine was explored through compounds with either a tertiary amine or amide, and the oxidation state of the sulfide was varied. Of note, the bis(4-F-phenyl)methyl moiety of the previous lead compounds (JJC8-091, JJC8-088, and JJC8-089) was retained in these new series [51]. Several compounds were designed and synthesized in this series with terminally attached alkyl-phenyl and para-substituted phenyl moieties.

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Table 4.4  Binding affinities of aminopiperidine and piperidine amine-containing modafinil analogs DAT R1

SERT

σ1

Compound Scaffold Y

Z

R2 Ki ± SEM (nM)

5aa

A

S=O

C=O Phenyl

H

79.1 ± 20.6

7780 ± 734

585 ± 21.5

5bb

A

S=O

C=O 4-fluorophenyl

H

77.2 ± 4.54

4640 ± 381

1440 ± 131

4-fluorophenyl

26.5 ± 3.88

5cc

A

S=O

CH2

H

50.6 ± 11.2

373 ± 23.8

5dd

A

S

C=O 2,4-difluorophenyl

H

30.0 ± 8.25

296 ± 35.3

20.6 ± 2.38

5ee

A

S

CH2

Phenyl

H

32.9 ± 5.86

409 ± 58.2

3.81 ± 0.639 351 ± 25.9

5ff

A

S=O

CH2

1-OH-2-­phenylethyl H

91.8 ± 21.3

599 ± 54.4

5gg

A

S

CH2

1-OH-2-­phenylethyl H

31.4 ± 9.64

129 ± 33.4

309 ± 38.3

5hh

B

S

CH2

Phenyl

H

108 ± 17.5

331 ± 34.6

60.9 ± 8.90 41.4 ± 10.9

5ii

B

S

CH2

4-fluorophenyl

H

55.9 ± 6.08

268 ± 9.33

5jj

B

S

CH2

1-OH-2-­phenylethyl H

47.7 ± 2.62

66.8 ± 2.82

88 ± 4.02

5kk

A

S

C=O 2,4-difluorophenyl

30.0 ± 8.25

296 ± 35.3

20.6 ± 2.38

H

The aminopiperidines were slightly more potent than the piperidine amine analogs; however, the trend was opposite with 2-OH-propylphenyl-substituted analogs. Reduced sulfides were slightly more potent than their sulfoxide counterparts with a moderate loss in DAT selectivity compared to SERT (5ff versus 5gg). Overall, all compounds resulted in moderate binding affinity for DAT and relatively improved potency towards SERT.  This series of compounds was also explored for activity against σ1 receptors due to preclinical precedence related to the therapeutic value of dual DAT/ σ1 inhibitors [52]. All compounds were inactive towards NET. The most promising among this series of compounds were 5bb, 5cc, and 5dd, with highest stability, which were carried forward for further in  vitro and in  vivo evaluation. None of these analogues showed a cocaine-like profile as systemic administration produced only minimal stimulation of ambulatory activity. Kalaba et al. [53] have reported another series where the carboxamide of modafinil is replaced with a number of five- and six-membered aromatic heterocycles to improve activity and selectivity and in vitro/in vivo profiles (Table 4.5).

Compound 5ll from this SAR studies was one prototype with comparable DAT potency as modafinil, and negligible activity towards SERT and NET. Compounds 5mm and 5nn were almost fivefold more potent than modafinil against DAT and also were inactive against SERT and NET. Larger, bulkier substituents in place of methyl or cyclopropyl of 5mm and 5nn resulted in two- to threefold loss in potency (5oo to 5pp). However, a chloro substituent was well tolerated (5oo). Para-­ substitutions at the diphenyl rings (dimethyl in 5qq and difluoro in 5rr) continued

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Table 4.5  Inhibition of DAT, NET, and SERT-mediated uptake of respective radioligands by thiazolecontaining modafinil analogues

Compound Scaffold X

Z

n A B

5ll

A

H

–

– H H

5mm

B

H

S=O 1 H CH3

DAT (IC50 ± SD, μM)

NET (IC50 ± SD, μM)

SERT (IC50 ± SD, μM)

14.73

420.1

NA

3.25

174

NA 436.1 ± 129

5nn

B

H

S=O 1 H Cyclopropyl 4.1 ± 0.8

687.2 ± 152.8

5oo

B

H

S=O 1 H n-propyl

28.43 ± 1.93

NA

NA

5pp

B

H

S=O 1 H n-butyl

13.50 ± 2.76

164 ± 56.88

NA

5qq

B

CH3

S=O 1 H H

7.32 ± 0.04

NA

NA

5rr

B

F

S=O 1 H H

6.76 ± 0.67

NA

NA

5ss

C

CH3

–

– –

–

10.57 ± 0.80

215.50 ± 66.01

NA

5tt

C

OCH3 –

– –

–

71.59 ± 8.28

NA

NA

5uu

–

–

– –

–

0.65 ± 0.07

73.25 ± 9.15

NA

–

to provide highly potent and selective compounds in this series. Other analogs with thiazole ring linked to the main scaffold via 2- and 5-position led to reduced potency. The authors have also reported results of chiral separation of several analogs with promising potency and selectivity. One of the chiral HPLC separation products (5uu, Table 4.5) displayed highest DAT activity (IC50 = 0.65 ± 0.07 μM) and 100-­ fold less active on NET (IC50 = 73 ± 9 μM) and inactive for SERT. Hence, this series of compounds also represent potential new leads for developing psychostimulant therapeutics. Overall, the SAR studies of modafinil analogs provide promising new leads to develop drugs with an atypical DAT inhibitor profile that could have utility as anti-addiction therapies. Discovery of such atypical DAT inhibitors that lack “cocaine-like” profile piqued further interest in determining their molecular interactions with DAT. It is suggested that these ligands bind and stabilize a DAT conformation which is disparate from that of cocaine-bound DAT conformation resulting in contrasting psychostimulant effects. Experimental evidence suggest that cocaine stabilizes outward-open DAT conformation whereas JHW-007, GBR-12909, modafinil, and its analogs tend to be less affected by conformational changes and most likely favor a more inward-facing occluded conformation [54]. This conformational “preference” could attribute to the lack of addiction potential of atypical inhibitors [55]. Another reason for reduced addiction liability of atypical DAT inhibitors could be their slow rate of onset of action in the brain or their off-target effects that might also contribute to their reduced behavioral reinforcing effects [55]. Hence, further studies related to specific structural basis of interaction of DAT ligands are needed to promote the discovery and development of improved medications for psychostimulant addiction. With the growing interest in the possible therapeutic potential of allosteric modulators of DAT, a library of diphenylmethyl (benzhydryl)-containing compounds were screened for their allosteric activity against the MATs (Fig.  4.2) [55, 56]. Among these, SRI-9804 (6a) was reported to inhibit both uptake and efflux of [3H]-dopamine, but only with partial efficacy (40–60%). Similar to allosteric

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activity of S-citalopram in SERT, SRI-9804 reduced the dissociation of a radioligand prebound in the orthosteric site of DAT. Two other compounds, SRI-20040 (6b) and SRI-20041 (6c), were eventually reported to partially inhibit [125I]RTI-55 binding and [3H]-DA uptake slow the dissociation rate of [125I]RTI-55 from the DAT, and allosterically modulate d-amphetamine-induced, DAT-mediated DA release. Subsequently, a series of SRI-20041 analogs were designed, synthesized, and evaluated in order to increase the affinity for DAT. This resulted in SRI-29574 (6d), one of the high-­affinity and selective DAT inhibitors in this series, showing similar pharmacological features to its parent compound. SRI-29574 partially inhibited DAT uptake (IC50 = 2.3 ± 0.4 nM) while being inactive in inhibiting DAT binding. The binding site of these compounds is still unknown, but regardless of their potential clinical application, their unconventional transporter pharmacology makes them potentially interesting candidates to further explore DAT allosteric modulators. Our group recently reported a novel allosteric inhibitor of DAT known as KM822 (7, Fig. 4.2) [25, 57]. KM822 was identified using in silico screening against the putative allosteric site present in the extracellular region of the DA translocation pathway. Biochemical investigation revealed it to be a noncompetitive inhibitor of DAT with relatively good selectivity. It was also shown to reduce psychostimulant-­ mediated stimulatory effects in various ex vivo and in vivo models of addiction and thus represent a possible candidate for exploring another novel class of drugs to treat addiction.

Fig. 4.2  Chemical structures of DAT allosteric ligands

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4.5.2 Structure-Activity Relationship Studies of SERT Ligands Several classes of antidepressant drugs that target SERT have been developed and have been classified as tricyclic antidepressants (TCAs), selective serotonin reuptake inhibitors (SSRIs), and serotonin-norepinephrine reuptake inhibitors (SNRIs) (Fig. 4.3). The first-generation antidepressants included the TCAs like imipramine (8), amitriptyline (9), desipramine (10), and clomipramine (11). However, due to their nonspecific effect on cholinergic, histaminergic, and α-adrenergic pathways and their low therapeutic index, their use now is limited to treatment-resistant patients who have failed to respond to newer generations of antidepressants [58]. In the search for highly efficient antidepressant drugs with an improved safety and tolerability profile, the considerable effort of the last five decades led to the development of the selective monoamine reuptake inhibitors, such as SSRIs. SSRIs are currently the most prescribed antidepressant pharmacotherapy and the most common SSRIs used till date are fluvoxamine (12), fluoxetine (13), citalopram (16), paroxetine (14), and sertraline (15). SSRIs have a diverse chemical structure, and, in many instances, they do not share common structural motifs. The structural explanation of how these diverse ligands bind to SERT have been summarized by Coleman and Gouaux [12] by obtaining and comparing X-ray crystal structures of SERT in complex with paroxetine, citalopram, sertraline, and fluvoxamine. The diversity of SSRI chemical structures, in turn, results in compounds with varied affinities towards SERT and substantial pharmacological differences. The most

Fig. 4.3  Chemical structures of clinically-approved SERT ligands

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studied SSRI to date is citalopram. It is the most SERT-selective SSRI.  The S-­enantiomer (16a) is responsible for the high selectivity and affinity for SERT and is ~30-fold more potent than R-citalopram (16b). In the past, several SAR studies on citalopram have been reported [59–61]. These SAR studies employing the analogues of citalopram have been pivotal in characterizing the S1 site for SERT [62, 63, 65, 76, 61]. More recently, the interest in achieving higher drug target selectivity to minimize side effects have led to an impetus in the study and development of SERT inhibitors that target the allosteric sites. The SSRIs like sertraline, paroxetine, clomipramine, and citalopram have been shown to possess allosteric activity as they can impair dissociation of a pre-bound high affinity radioligand to the transporter [74]. However, the allosteric potencies of these compounds are all in the micromolar range, while they bind to the orthosteric site with low-nanomolar affinity [74]. The co-crystal structure of S-citalopram bound in the allosteric region of SERT has made it feasible to further explore and understand the allosteric regulation mechanism of MATs [11].

Banala and colleagues [64] were the initial ones to explore the SAR of citalopram analogs for binding at the S2 site by measuring the ability to decrease the dissociation rate of [3H]-S-citalopram from the S1 site via allosteric modulation at S2 (Table 4.6). All compounds were initially assessed for SERT-S1 potency by competitive radioligand binding displacement of [3H]-S-citalopram. The replacement of 5-CN substituent with amide, amino, or any other aliphatic heterocyclic groups (compounds 16c to 16g) resulted in a decrease in the SERT S1 binding affinity compared to citalopram but only marginally changed for the aldehyde substitution (16d). With exception of the amide (16c), all other replacements retained high SERT selectivity versus NET. Substitution with bulkier heterocycles or substituted aryl rings also reduced affinity with a few exceptions. Substitutions 4-nitrophenyl (16h) and 4-aminophenyl (16i) reduced SERT-S1 binding almost 20-fold. However, these two compounds displayed allosteric site S1 binding by prolonging the dissociation of the S1 radioligand. For the 4′-fluoro phenyl moiety, replacing 4′-fluoro with bulky substituted aryls (e.g., 16j) decreased the SERT-S1 binding affinity, no binding at SERT-S2 site. Replacement of a methyl group of dimethyl amine moiety with bulky long chain aryl or heterocycles (compounds 16k to 16m) reduced both SERT-S1 affinity and selectivity; however, some of these compounds showed SERT-­S2 binding.

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Table 4.6 Citalopram analogues assessed by radioligand binding displacement of [3H]-escitalopram (for SERT), tritiated-nisoxetine (for NET), and potency of 30 μM compound in inhibiting dissociation of [3H]-escitalopram from SERT

Compound Citalopram (16) S-citalopram (16a) 16c 16d 16e 16f

R1 CN

R2 F

R3 CH3

SERT (Ki ± SEM, nM) 1.94 ± 0.198

CN

F

CH3

0.89 ± 0.132 10500 ± 893 68 ± 12

CONH2 CHO CH2NH2

F F F F

CH3 CH3 CH3 CH3

17.7 ± 1.80 4.3 ± 0.096 41.9 ± 5.73 3.24 ± 0.328

F

CH3

22.7 ± 2.62 NA

24.8 ± 1.1

CH3 CH3 CH3

18.6 ± 1.65 8280 ± 825 29.2 ± 4.11 ND 51.5 ± 6.63 2800 ± 353

40.2 ± 7.0 52.6 ± 4.1 NA

C4H9

61.6 ± 6.19 276 ± 41.1 22.8 ± 2.29 ND

NA 59.6 ± 1.0

98.8 ± 13.3 272 ± 48.5

60.1 ± 1.0

16g 16h 16i 16j

NET (Ki ± SEM, nM) 5950 ± 77.4

[3H] escitalopram dissoc. t1/2 (min) 16.1 ± 1.0

16k 16l

4-nitrophenyl F 4-aminophenyl F CN 3cyanophenyl CN F CN F

16m

CN

F

123 ± 17.7 NA NA 11100 ±  1490

NA NA 17.4 ± 0.8 16.4 ± 0.3

NA not active

Larsen et  al. [68] performed a systematic SAR study on citalopram (which is >1000-fold selective for S1 than S2) to identify S2 selective compounds by exploring all possible combinations of substituents between citalopram and talopram (Table 4.7, 16n, a close analog of citalopram and only possess low SERT-S1 affinity) [63]. The authors measured the IC50 for inhibition of [3H]-S-citalopram dissociation by determining the [3H]-S-citalopram dissociation rates in the presence of increasing concentrations of allosteric inhibitor [21]. The authors concluded that – CN group (absent in talopram) is absolutely necessary for S2 activity. Compounds

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Table 4.7  Systematic SAR exploration of citalopram and talopram analogs

Compound Escitalopram (16a) Talopram (16n) 16o 16p 16q

SERT S1 binding IC50 (μM) X Y Z R CN F H CH3 0.010 [0.0008; 0.013] 0.718 H H CH3 H CN F H

H

0.041 [0.032; 0.051] CN F CH3 CH3 6.4 [4.7; 8.8] CN H CH3 CH3 10 [9.2; 12]

T1/2 for [3H]S-CIT dissociation (min) 790 ± 160

SERT allosteric potency IC50 (μM) 5.8 [5.4; 6.3]

100 ± 3.8

ND

380 ± 26

10.1 [10.0; 10.2]

1090 ± 130 440 ± 30

3.6 [3.3; 3.8] 12 [10; 13]

ND not determined

without –CN displayed a fivefold reduction in S2 potency compared to their –CN congeners. The presence of para-fluoro was also important for S2 activity but its removal did not affect the S1 activity much. The addition of phthalane dimethyl groups in ##3 as compared to citalopram markedly reduced S1 affinity with a significant increase in the allosteric potency. Changing the dimethyl amine to monosubstitution showed almost no change in S2 activity but a reduction in S1 activity. The compound with the highest allosteric potency and lowest orthosteric affinity reported was dimethyl citalopram (16p), with a twofold increase in the allosteric potency compared to the orthosteric affinity [68]. The tested compounds were all racemic mixtures. To date, investigation of the enantioselectivity of these compounds has not been reported. A recent in silico screening of a library of citalopram analogs and subsequent in vitro evaluation for their allosteric potency led to the discovery of Lu AF60097 (17, Fig.  4.4) with an allosteric potency of 31  nM (measure of imipramine ­dissociation inhibition at S1), which is more than a 150-fold increase compared with citalopram [74]. Lu AF60097 also possess a S1 binding component with SERT S1 binding potency of ~265  nM and hence could be another template for future SAR studies to isolate S2 selective compounds. Another potential allosteric modulator of recent interest is vilazodone (18, Fig. 4.4). Vilazodone is an approved antidepressant with partial agonist activity at 5-HT1A receptor. Recent molecular pharmacology and cryo-EM structural elucidation have revealed that vilazodone’s primary binding site is the allosteric site S2 [22], as opposed to previously reported results of MD simulations that had suggested that vilazodone binds to the S1 site similarly to all other TCAs and SSRIs [80]. Vilazodone inhibits [3H]5-HT transport with an apparent Ki of 1.1 nM and causes a decrease in the VMAX of [3H]5-HT without having any significant effect on KM suggesting a noncompetitive binding with 5-HT.  Vilazodone also inhibits [3H]-imipramine dissociation with an allosteric potency of 14 nM and [3H]S-citalopram dissociation with an allosteric potency of 250 nM. The high-­affinity profile of such allosteric compounds along with the elucidation of the molecular binding structures opens the possibility of developing compounds with beneficial therapeutic profiles.

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Fig. 4.4  Structures of SERT allosteric ligands

4.5.3 Structure-Activity Relationship Studies of NET Ligands Ligands of NET are commonly classified into: selective norepinephrine reuptake inhibitors (sNRIs), serotonin-norepinephrine reuptake inhibitors (SNRIs), norepinephrine-­dopamine reuptake inhibitors, and triple reuptake inhibitors (TRIs). Selective NRIs (Fig. 4.5) such as nisoxetine (19), reboxetine (20), and atomoxetine (21) are useful in the treatment of depression and ADHD. Nisoxetine is a selective, potent NRI with (R)-nisoxetine much more potent than (S)-enantiomer. Reboxetine is marketed as a racemic mixture, with (+)-(S,S)-enantiomer is much more potent for NET inhibition as compared to SERT, with (−)-(R,R)-enantiomer gaining potency for SERT. Substitutions at the aryloxy ether group affected the selectivity of compounds between NET and SERT, and in general, the (S,S)-enantiomers were more potent for NET than SERT. Several SAR studies have been reported for reboxetine where the aryloxy ether group is replaced by a number of substituted arylthiol-­ ether functionalities which in general retain the potency against NET. Atomoxetine was developed and launched by Eli Lilly as a treatment for ADHD and is a potent, selective inhibitor of NET. It is an (−)-isomer of an ortho-methylphenoxy analog of nisoxetine, and is a derivative of phenoxypropylamine. Its mechanism of action in the treatment of ADHD is unclear but is thought to be related to its selective inhibition of presynaptic norepinephrine reuptake in the prefrontal cortex, resulting in increased noradrenergic transmission, important for attention, learning, memory, and adaptive response [66]. The X-ray crystal structure of dDAT with nisoxetine and reboxetine exhibit outward-open conformations with inhibitors bound in the central S1 pocket provide insights into the pharmacophores that dictate selectivity towards hNET [9]. The new generation of antidepressants has seen a paradigm shift where a mixed action on both SERT and NET is desirable to achieve additional therapeutic benefits such as improved antidepressant efficacy and faster onset of action. Approved SNRIs such as duloxetine (22), milnacipran (23), and venlafaxine (25) may have improved antidepressant efficacy. In another study, X-ray crystal structures of dDAT with NE as well as SNRIs duloxetine and milnacipran were

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Fig. 4.5  Structures of NET ligands

identified. Bupropion (24) belongs to the NDRI class of dual reuptake inhibitors and has been approved to treat major depressive disorder (MDD) and for smoking cessation [70]. Despite the approval of several antidepressants, they still lack satisfactory therapeutic effect due to the low remission rates and delayed therapeutic onset, especially in the case of major depressive disorder (MDD) [67]. TRIs which inhibit all three transporters (DAT, NET, and SERT) are currently of great interest and several compounds have advanced into clinical trials (Fig. 4.6). Such polypharmacological profile of TRIs has led to their better efficacy, safety, and less tolerance in clinical evaluation for MDD, ADHD, binge eating disorder, and cocaine addiction [77]. One of the earliest TRIs developed was compound 26a that reached clinical trials for pain treatment [79]. Extensive SAR analysis of 26a was conducted by industrial groups to develop compounds with superior potency at all three transporters. Compounds 26b, 26c, and 26d that emerged from the SAR studies on 26a are also in the clinical development stage for ADHD and depression. Amitifadine (26c) is currently in a Phase 3 trial for MDD, and centanafadine (26d) is in a Phase 3 trial for MDD and ADHD. NS2359, another promising TRI currently in a Phase 2 clinical trial for cocaine addiction, MDD, and ADHD, was developed through structural modifications on naturally occurring TRI, cocaine. Dasotraline, 27 was discovered as part of SAR development around cis-sertraline. Tu et al. [78] have recently compared the binding modes of dasotraline (27), NS2359 (28), and centanafadine (26d) by docking them into the central binding sites of the crystal structure of SERT, and the homology models of DAT and NET, and created a pharmacophore model for TRI binding to understand their polypharmacological profile which could be useful in discovering new and improved TRIs.

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Fig. 4.6  Structures of TRIs currently under clinical investigation

Recently, a number of 4-benzylpiperidine carboxamides were explored as TRIs (Table  4.8) [72]. The potency was compared to venlafaxine, the control drug for SERT and NET activity, and GBR12909 to compare DAT potency. In general, changing 3-carbon linker to 2-carbon drastically improved DAT inhibition with no change in NET and SERT inhibition (example, compound 29c versus 29d). The authors found that they could modulate the inhibition of DAT, NET, and SERT by changing the R substituents. Although most R substituents provided high potency at NET, 4-biphenyl substitution (with 3-carbon linker) provided exceptionally high inhibitory potency against NET and SERT (29a). Another novel compound, LPM580098 (toludesvenlafaxine, Fig. 4.5, compound 25b), was designed and synthesized based on the structure of venlafaxine and was reported to show promising preclinical results in neuropathic pain models [69]. It is a prodrug that can quickly convert to the SNRI desvenlafaxine (25a) under the hydrolysis of ubiquitous esterase in vivo [81]. Another series of TRIs reported recently contain the asymmetric pyran scaffold (Table 4.9) [75].

S. Aggarwal and O. V. Mortensen

122

Table 4.8  SAR exploration of 4-benzylpiperidine carboxamide containing TRIs

Compound 29a 29b 29c 29d Venlafaxine GBR12909

N 3 2 3 2 – –

R 4-biphenyl 4-biphenyl 2-naphthyl 2-naphthyl – –

SERT NET DAT IC50 (in μM) are shown as 95% confidence intervals 0.04–0.07 0.01–2.12 >10 0.986 0.17–1.28 >10 0.06–0.18 0.15–0.76 >10 0.39–1.31 0.28–0.57 0.71–3.70 0.07–0.52 2.16–3.01 – – – 0.02–0.08

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Table 4.9  Systematic SAR exploration of pyran-based TRIs Compound 30a 30b 30c 30d 30e 30f 30g 30h 30i

DAT (Ki, nM) 13.3 ± 2.0 16.2 ± 1.5 29.8 ± 4.1 7.94 ± 0.66 182 ± 50 24.5 ± 1.2 29.6 ± 6.9 56.3 ± 1.1 6.29 ± 1.52

NET (Ki, nM) 13.2 ± 3.5 3.23 ± 0.99 524 ± 132 14.6 (6) ± 2.9 27.9 ± 4.9 3.92 (5) ± 0.71 2.14 ± 0.58 20.8 ± 4.6 6.74 ± 1.80

SERT (Ki, nM) 46.7 ± 17.0 16.2 ± 1.5 259 ± 77 367 ± 52 1540 ± 299 339 ± 39 1.72 ± 0.48 13.6 ± 1.6 30.1 ± 5.3

Fig. 4.7  Prototype of 1,5-disubstituted tetrazole series of TRIs

The authors used extensive SAR studies to map out the structural requirements for interaction of the pyran derivatives with MATs to design superior TRIs (Table 4.9). The group had previously reported compounds 30a and 30b as orally active TRIs with high efficacy in the rat animal model of depression. Molecular docking studies have revealed that 30b makes strong, conserved H-bonds and hydrophobic interactions within the S1 site of all three transporters. Further modification of the aryl ring of N-benzyl moieties of 30a and 30b provided compounds with varying degrees of potency against the three transporters. Subtle changes in the aryl ring substitution, e.g., comparing 30c and 30d, and drastic changes in potency are observed within the two positional isomers, with DAT and SERT potencies only moderately affected. The para-fluoro substitutions on the biphenyl rings were important for TRI activity as their removal (30e versus 30f) resulted in tenfold reduction in NET potency, sevenfold reduction in DAT activity, and fivefold decrease in SERT inhibition. The importance of (S)-hydroxyl was evident when it was removed from 30g to get 30h resulting in tenfold reduction in NET and SERT activity, but only a moderate decrease in DAT potency. Inverting the stereochemistry of hydroxyl from axial position in 30a to equatorial position to get 30i slightly improved the TRI activity as compared to 30a. Paudel et al. have designed, synthesized, and analyzed the SAR of another promising class of TRIs with the 1,5-disubstituted tetrazole scaffold [71, 73]. The prototype compound 31 (Fig. 4.7) in this series showed potent inhibitory activity against the three reuptake transporters (IC50; 158.7 nM for 5-HT; 99 nM for NE; 97.5 nM for DA).

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In conclusion, several SAR studies are currently in place to characterize novel TRI compounds that can be further utilized for developing better therapeutic agents against neurological disorders.

4.6 Conclusion DAT, NET, and SERT represent important therapeutic targets for a number of CNS-­ related pathophysiological conditions. The discovery of crystal structures of transporter homologs bound with substrate and inhibitors and corresponding homology-based computational studies have substantially progressed our understanding of structure-function profiles of MATs and has aided in several medicinal chemistry-based drug discovery efforts. Over the years, a multitude of drug classes have been explored mainly via ligand-based drug design and discovery. These compounds target the MATs with unique and interesting behavioral profiles and have been explored as a promising starting point for developing therapeutics against various neurological disorders. Because the vastness of the literature available on SAR studies of MATs is substantial and beyond the scope of this review, we have attempted to summarize the most recent developments that have been made targeting each of the transporters with a particular focus on drug developments that have resulted in unique and superior behavioral effects.

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Chapter 5

Drug Development for New Psychiatric Drug Therapies M. Lynn Crismon, Janet Walkow, and Roger W. Sommi

Abstract  Drug development is an expensive, high risk, and highly regulated process. Only about 6.2% of new molecules tested for mental disorders eventually achieve Food and Drug Administration (FDA) approval. New molecular entities are produced, and extensive in vitro animal testing is performed before they are evaluated in humans. The compound is used in animals to predict clinical effects in humans, and studies addressing pharmacodynamics, pharmacokinetics, toxicology, and mutagenicity are conducted. Human research proceeds in three stages with the ultimate goal of proving that a new agent is efficacious and safe for a treatment of a specific disease in humans. If efficacy and safety are demonstrated in two Phase III studies, then the sponsor can submit a new drug application (NDA) to the FDA. The FDA oversees each step of the process to assure that good research practices are followed, data integrity is assured, and human research subjects are protected. Keywords  Drug development · Clinical trial · FDA · Biomarker · Animal models · Psychotropic · Regulation · Pharmacokinetics · Pharmacodynamics · Efficacy · Safety Innovations in healthcare products or services have the potential to positively impact society; however, taking an early discovery or idea to the clinic is a daunting challenge. Along the way, these technologies face roadblocks unique to healthcare. The drug development pathway (Fig. 5.1) details the various steps and regulatory requirements that guide the development of new psychiatric drug therapies. A strong

M. L. Crismon (*) · J. Walkow The University of Texas at Austin, Austin, TX, USA e-mail: [email protected]; [email protected] R. W. Sommi University of Missouri at Kansas City, Kansas City, MO, USA e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 M. Macaluso et al. (eds.), Drug Development in Psychiatry, Advances in Neurobiology 30, https://doi.org/10.1007/978-3-031-21054-9_5

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Drug Development: The R&D Process

Pre-Discovery

Drug Discovery

5,00020,000 compounds

Preclinical

250 compounds

o

FDA Review

Clinical Trials

5 compounds Phase I

Phase 2

Phase 3

20-100 volunteers

100-500 volunteers

1,000-5,000 volunteers

3-6 Years

PostMarkeng

One FDA Approved Drug

0.5-2 Years

6-7 Years IND Submitted

Manufacture

Ongoing

NDA Submitted

Fig. 5.1  The research and development process. Adapted from the American Association for Cancer Research [3]

understanding of the processes, regulatory requirements, timelines, and the impact they have on developing and commercializing new psychiatric drug products is essential for understanding the timing, cost, and complexity involved for each product that is commercialized. The goal of drug development is to find and provide new drugs that we can depend on to improve our health and quality of life. Psychotropic medications are used to treat the symptoms associated with a variety of mental disorders. These therapies exert effects on the brain and nervous system, as well as other organ systems, and they undergo extensive development and testing before becoming a prescription product. The pathway for new drug therapies to be approved by the Food & Drug Administration (FDA) is highly regulated to ensure the efficacy, safety, and quality of these medicines. Understanding the steps involved, the clinical components, and the FDA’s role in approving new psychiatric therapies provides important context for researchers, clinicians, and other health professionals.  The information presented in this chapter reflects the current US practices and regulatory guidelines unless otherwise noted.

5.1 The Drug Development Pathway Drug development starts with discovery of a new molecule which, if successful, proceeds through in vitro studies, animal studies, studies in healthy individuals, and proceeding to studies in people with the disorder of interest. If found to be both efficacious and safe, then a new drug application is submitted to the FDA.

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5.1.1 Pathway Overview There are four distinct stages of the pathway for developing new drug therapies. The process for evaluating and identifying the best candidates to advance is time-­ consuming and expensive. It can take between 10 and 14 years and cost billions to develop a therapy with the characteristics to achieve a specific, desired result. The earliest stage, discovery/preclinical, includes all of the activities before a new drug therapy advances into human clinical trials. The first part, drug discovery, involves researchers scanning up to tens of thousands of potential compounds before identifying lead candidates for a specific disease. This process identifies up to 250 compounds to move forward for more detailed evaluation. The lead candidates progress to the preclinical phase for further characterization, experiments, and formulation development into the most suitable forms for the specific treatment, including a tablet, capsule, orally dissolving tablet, injectable, intravenous solution, topical patch, or inhaled product. As potential drug candidates go through this stage, the number narrows to a limited number (five or fewer) that will advance into clinical trials. Once the preclinical work has progressed sufficiently, an investigational new drug (IND) application is filed. The FDA reviews the application and decides whether there is enough information to allow a product to proceed to human clinical trials. Only those with the best potential to achieve specific clinical results will move into this stage. Once a product is approved by the FDA to enter clinical trials, a clinical development plan (CDP) is developed and reviewed with the FDA to define how the clinical trials will be conducted. The clinical trials consist of three stages, typically starting with a small group of healthy volunteers (Phase I) to determine the safety and basic pharmacokinetics of the test product, to large studies involving hundreds to a thousand or more patients at multiple study sites (Phase III). In order to progress from one phase to the next, the FDA must review the data and decide whether to allow the studies to progress to the next phase. The third stage that encompasses regulatory review by the FDA is the manufacturing processes. These activities take place as early as the drug discovery and preclinical phases. Throughout the development pathway, regulatory activities and efforts to scale up production of the active therapeutic ingredient (ATI) as well as the final formulation are occurring. The investigational new drug (IND) application is filed during the preclinical phase, and a new drug application (NDA) can be filed with the FDA for review and potential approval following completion of Phase III clinical trials. From the original thousands of compounds identified in the discovery phase, only one will typically make it all the way through the process and be approved by the FDA for commercialization. Following the approval of a new drug product, ongoing monitoring of compliance with manufacturing and distribution processes must occur. In addition, information concerning adverse effects is collected over a long period of time. Clinical trials are limited to hundreds to perhaps over a thousand people, and it is often not obvious which adverse effects are most prominent or problematic until many more

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patients have been treated. It may take years to answer whether certain adverse effects, particularly those that are rare but potentially serious, are problematic and those effects are addressed in the fourth stage that is often referred to as Phase IV, post-marketing surveillance programs, which assess patient safety and quality of life as well as drug product effectiveness.

5.1.2 Drug Development Costs As indicated in Fig. 5.2, developing new drug therapies is a massive investment in time and resources. In the 1980s, the cost to develop a new drug product was approximately $100 million. A 2014 report found the cost to develop a prescription drug had reached $2.6 billion [20]. Over four decades the cost has risen exponentially. Examination of the cost per development stage reveals small increases in discovery, accelerating costs in preclinical, and the most significant increases occurring in the clinical trials (Phases I, II, and III). Only launch and discovery costs appear to have decreased, likely attributed to the reduced costs of digital advertising and newer, high-throughput screening tools used in early discovery [20]. Part of this cost is driven by the fact that only about 9.6% of all compounds across all therapeutic areas are FDA approved and reach the market. This is even lower in psychiatry (6.2%) and neurology (8.4%). The Phase III clinical trials’ failure rate with central nervous system (CNS) acting agents is significantly higher than with other types of agents, and it is estimated that the Phase III clinical trial failure rate is 20% higher than in other therapeutic areas [39]. This has prompted pharmaceutical companies to be both cautious and strategic in deciding the types of compounds to develop. [38, 69]. Since the 1990s, drug development costs have more than doubled, with the largest cost increase being in human clinical trials. Adapted from O’Hagan [59], Life Size VC [53], Policy and Medicine [61].

Fig. 5.2  Increase in drug development costs over time

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Between 2009 and 2018, it was estimated to cost between $314 million and $2.8 billion to bring a new therapeutic entity to market, including the capitalized R&D cost per product and expenditures on failed trials [77].

5.1.3 Regulatory Overview The approval pathways for drug therapies can be complex, time-consuming, and expensive. The regulatory tools that have been developed to certify compliance and efficacy of new medicines are designed to ensure the safety and integrity of every product before it can be approved for commercialization. Most take for granted that drug therapies are safe if they are approved for commercialization and sale – a good assumption since FDA’s involvement starts early in the development process and continues after a product is commercialized. The FDA becomes involved in the preclinical phase, when the sponsor identifies a lead molecule and plans to prepare for testing its therapeutic potential in human clinical trials. This is when regulations become a prominent part of developing the strategy for advancing a product. The regulations that are required or authorized by statute are published in the Federal Register, the US government’s official publication for notifying the public of agency actions. The procedures that health innovators follow come from US laws, executive orders, and FDA regulations that can be found in the Code of Federal Regulations (CFR). Regulations that apply to the FDA’s oversight of food and drugs are found in Section 21 of the CFR [15]. These regulations document all actions required of drug sponsors under federal law. To better understand how FDA regulations align with the R&D timeline, the development pathway is depicted in Fig. 5.3, including the key regulatory elements as they relate to the development pathway. Drug development is a highly regulated process, with the Food and Drug Administration carefully monitoring and evaluating each step of the process. Developed from [28]. These will be discussed in greater depth in the preclinical, clinical, regulatory, and post-marketing sections.

5.1.4 Types of Drug Therapies Drug therapies fall into several categories: new molecular entities (NME), therapeutic biologics, generics, biosimilars, over-the-counter (OTC) drugs, vaccines, blood products, and cellular and gene therapy products. New psychiatric drug products are currently prescription products in the NME category.

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Phases of Drug Development Preclinical Phase

Preclinical Tes ng

IND Submission

GLP

Clinical Phase

FDA Review Phase

Clinical Trials/IND Maintenance GCP

IND = Invesgaonal New Drug NDA = New Drug Applicaon BLA = Biologic License Agreement

NDA/BLA Submission & Review

Post-Market Phase

Drug Marke ng & Post-Marke ng Requirements GMP

GLP = Good Laboratory Pracces GCP = Good Clinical Pracces GMP = Good Manufacturing Pracces

Fig. 5.3  Regulatory components of drug development

New Molecular Entities The development and approval of new molecules and biological therapies are handled by CDER. This FDA branch also oversees nonprescription, or OTC drugs as well as the process for moving an approved prescription (Rx) product to OTC status, called an Rx-to-OTC switch. Generics Generics are copies of innovator or brand-name prescription drugs and comprise almost 90 percent of all prescriptions dispensed in the United States [7]. Generic drug developers are allowed to use data generated by brand-name companies for efficacy and safety, resulting in significantly lower development costs and lower prices for patients. The Hatch-Waxman Act of 1984 established patent exclusivity protections for drug innovators and granted generic companies access to regulatory approval by filing an abbreviated NDA (ANDA). To achieve FDA approval, the manufacturer must demonstrate that the generic product has bioavailability similar to the innovator product. To be considered bioequivalent, the generic product must have a peak plasma concentration, time to peak plasma concentration, and total amount of drug absorbed (area under the curve) that is not statistically different from the innovator’s product. These studies are typically crossover studies in a small number of healthy male subjects, using the subject as his own control

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5.2 Preclinical Drug Development Phase The preclinical phase is a robust transition with the overall goal of predicting whether a compound will be beneficial in treating a particular disease. Activities focus on evaluating drug molecules from the discovery phase.

5.2.1 Characterization A primary job of the pharmaceutical formulation scientist is determining how best to formulate and deliver a compound to its site of action in the body, while ensuring that it remains stable over time. The starting point of this process focuses on obtaining a greater understanding of the lead compound itself and determining the physical and chemical properties of the lead compound. Larger quantities of the drug molecules are made so that they can be tested to gauge their solubility in various liquids, sensitivity to light or heat, chemical stability, and interactions with other materials. All of these important properties need to be evaluated and addressed before attempting to incorporate an active compound into a dosage form. These answers play a large role in the stability of a dosage form, how available it is at its target site of action, the most appropriate storage conditions, and how the drug product should be manufactured.

5.2.2 Developing a Formulation Prototype Characterizing the drug molecules, coupled with knowledge of the disease or condition being treated, as well as the patient population, informs the type of formulation that should be considered, whether it is preferred as a tablet, capsule, orally disintegrating tablet, injectable, inhaled product, nasal spray, topical cream/ointment, or transdermal patch. The selection is based on the drug’s chemical and physical properties with consideration of patient population needs. Another consideration is the release rate – whether a rapid release or extended release formulation is preferred to reach appropriate dosing levels in a specific clinical condition. Patient adherence may be impacted by the dosing schedule, and extended release products that require only daily or twice daily doses can be helpful for medication adherence. Similarly, long-acting injectable products may allow parenteral administration every few weeks or months.

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In psychiatry, several interesting developments occur beyond oral formulations that are directed at specific clinical management challenges. Specifically, it is important to address  administration of medications during an acute crisis where patients may be combative and uncooperative and treatment nonadherent. Other formulations may address either tolerability or unique oral absorption challenges. Some examples of strategies to counter the acute crisis situation are the use of oral solutions and orally disintegrating tablets – where the clinician has some confirmation that the patient has actually swallowed the medication or that the drug will be absorbed through the oral mucosa. Immediate acting injections allow quick onset but may be less acceptable to patients. Other novel formulations include inhaled loxapine [19] which results in rapid absorption and onset of action. Challenges with overcoming barriers with medication adherence have been addressed principally with improving the drug’s tolerability and the development of long-acting injectable (LAI) formulations. In psychiatry most of the LAI development has been with antipsychotics. LAI development incorporates molecular strategies including using prodrugs (esters) and/or physical strategies of using oils, polymers, gels, and manipulation of particle size with the ultimate goal of delaying absorption to the point the drug can be administered in intervals of weeks to months. Marketed products include the use of esterified molecules delivered in sesame oil, drug molecules trapped in glycolide/lactide microspheres, crystallization and grinding processes to create various particle sizes of relatively insoluble ester salts, and the use of gels which essentially form an implant that slowly dissolves and releases drug. Challenges to counter absorption and tolerability include the use of patches and sublingual formulations. Selegiline patches allow for the absorption of the drug with clinically relevant CNS concentrations while minimizing the inhibition of MAO-A in the gut – improving the tolerability and limiting the risk of dietary tyramine interactions [18]. Asenapine is available as a sublingually absorbed formulation as the bioavailability is drastically reduced if swallowed. More recently, an asenapine patch formulation allows for absorption of the drug without the issue of dysgeusia limiting its use. Other antipsychotic patch formulations are currently in development [1]. In addition to solving issues around oral absorption, administration in a crisis, or enhancing adherence, the use of oral solutions, orally disintegrating tablets, and patches provides a pathway to drug administration for patients unable to swallow capsules or tablets or who are restricted from taking medications orally. The use of prodrugs is another method to potentially avoid drug related complications. A prodrug is inactive pharmacologically but is metabolized in the body to the active form. An example is lisdexamfetamine which is hydrolyzed in the blood to amphetamine. Lisdexamfetamine has potentially less abuse potential than amphetamine, even when administered intravenously [54].

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5.2.3 In Vitro-in Vivo Testing The material characterization and early formulation studies of a lead compound are performed using a variety of equipment and in vitro testing methods. These provide important information to assess whether to proceed to in vivo studies. This is a noteworthy transition point, as the in  vivo studies require extensive knowledge and experience to design, conduct, and analyze the results. Significant effort is taken in selecting formulations to include in the in vivo studies, as they require substantial time and cost commitments. The early and later stage pharmacokinetic-pharmacodynamic (PK-PD) studies will often begin with rodents and may expand to other, more specific animal models for the intended disease target. It is common for one or more formulations to be evaluated in the early in vivo studies to observe differences in effectiveness, tolerability, and adverse effects that can lead to choosing a lead formulation or deciding that it needs to be re-engineered. At the same time, the in vivo studies are occurring, the formulations being tested in animals are often undergoing stability studies at various temperatures, light conditions, and humidity. These parallel activities can serve to expedite moving through the preclinical phase.

5.2.4 Pharmacokinetic-Pharmacodynamic (PK-PD) Analysis The PK-PD analysis examines the drug concentration in a body compartment  – most commonly venous blood – and relates it to the drug’s effect. The bioanalysis provides an estimate of the molecule’s safety and efficacy. Animal studies can provide a pharmacokinetic profile that shows how well the drug products are absorbed, distributed, metabolized, and excreted. Drug absorption refers to the percent of administered drug that ultimately reaches the circulation, also referred to as the drug’s bioavailability. For example, intravenous medications have 100% bioavailability; however, other routes of administration and formulation are generally lower since they may be absorbed in the intestine or be subject to first pass metabolism in the liver. Bioavailability in preclinical and clinical studies is determined by plotting the blood concentration as a function of time and referred to as the area under the curve (AUC). Biomarker selection and correlation with clinical endpoints are important for successful PK-PD modeling and provide predictive value in drug development, if they reflect the mechanism of action for intervention, whether or not they are surrogate endpoints [16]. Identification of biomarkers that can be used for predictive clinical assessment of disease progression can help measure the effect of drug interventions.

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The results of the PK-PD studies provide information on how to refine drug administration, evaluating whether the dose needs to be adjusted or deciding if the formulation needs to be changed. The studies may show that the drug or its metabolites stay in the body a short time, making it necessary to take several doses a day or develop a sustained release formulation. Psychotropic drug development has been limited in that a mental disorder diagnosis is based upon clinical phenotypes which likely represent substantial heterogeneity in etiology and pathophysiology [9]. In fact, the specific pathophysiology of mental disorders is currently unknown. Therefore, specific pharmacological mechanisms of action are used for heterogenous disorders. Serendipity has played a major role in the discovery of psychotropic medications, particularly during their first few decades of development. This is best represented by the fact that chlorpromazine was first investigated as a potential medication for “surgical shock” largely based upon its antihistaminic properties. Although ineffective for this purpose, the French surgeon Henri Laborit noted that patients experienced “no loss of consciousness, no change in the patient’s mentality but a slight tendency to sleep and above all ‘disinterest’ for all that goes on around him” [71]. Based upon his observations, he encouraged psychiatrists to use it in patients with psychosis, and it was subsequently developed as the first modern era antipsychotic. Animal Models Animal models have significant limitations when used to study mental disorders and the effects of medications. Rodents do not express the same range of emotions as humans, and the neural circuits are not nearly as complex [65]. Traditionally, the animal models used to predict efficacy of a medication for a particular mental disorder were developed based upon a behavior, and if it affected that behavior, then the mechanism of action was explored [17]. For example, early animal models of antipsychotic effect were dependent on a drug’s ability to produce catalepsy [58]. Thus, developed antipsychotics were almost guaranteed to produce extrapyramidal adverse effects in humans. More recently, computational chemistry has been used to predict the mechanisms that specific compounds will have. However, psychotropic drugs are largely still not developed based upon a known pathophysiology for a given disorder. Although it is hoped that genetics may ultimately allow psychotropics to be developed for homogenous disorders that is currently not reality [9]. Animal models typically involve rodents  – rats or mice. The early developed animal models were based upon drugs that had been proven clinically effective. Thus, the models tended to predict efficacy for compounds that had similar mechanisms of action (e.g., action on the benzodiazepine receptor for anxiety and dopamine receptor antagonism for psychosis) [10]. Animal models are developed with the goal of having the following [10]: • Face validity – the behavioral and physiological response in the animals is identical or at least very similar to that seen in humans.

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• Predictive validity – drugs with clinical efficacy in a given disorder should produce the response in the animal model. • Construct validity  – the etiology of the behavior and the pathophysiology are similar in both the human and the animal model. Animal models are challenging in that our understanding of the pathophysiology of mental disorders is inadequate, and human and rodent behaviors are much different. Many of the symptoms and behaviors seen in human mental disorders are not present in other animals. Much of the time, the animal model does not correspond with human emotions such as depression or anxiety, but rather examines certain kinds of locomotor behavior in different conditions. Thus, construct validity is highly suspect, and this may be one potential explanation for the high failure rate of CNS acting compounds in clinical trials. Similar challenges exist for face validity since the etiopathophysiology of most mental disorders is unclear, and humans and other species have different behaviors. Predictive validity is complicated by the fact that animal models are validated based upon existing FDA-approved psychotropics that for the most part have only modest efficacy. This is further complicated by compounds being assessed in animals acutely while pharmacotherapy in humans is typically several months to years. [39]. Select animal models are briefly discussed below. Animal models for antipsychotics – Animal models involving the administration of either amphetamine or phencyclidine (PCP) are commonly used to screen compounds for potential antipsychotic effects. The amphetamine model is based upon the observation that amphetamine produces positive symptoms of psychosis in humans. Amphetamine produces excessive mesolimbic dopaminergic activity, resulting in spontaneous locomotor activity and stereotypy in animals. D2 receptor antagonists block these effects [51]. Chronic amphetamine administration produces desensitization with resulting deficits in learning and attention. Both first- and second-­generation antipsychotics have been shown to block desensitization. Phencyclidine (PCP) produces both positive and negative psychotic symptoms in humans and may be a better model for the symptoms associated with schizophrenia. The attentional set-shifting test (ASST) is used to assess executive function in rodent models. The animals must learn a rule and then shift their attention to a previously irrelevant stimulus. NMDA antagonists such as ketamine produce positive and negative symptoms as well as cognitive deficits. These effects are attenuated by antipsychotics as well as nicotinic agonists. Some deficits are reversed by second generation but not first-generation antipsychotics. Animal models of cognition are more predictive of human cognition than models for symptoms such as delusions or hallucinations. Prepulse inhibition (PPI) looks at suppression of a strong stimulus by a small stimulus. Antipsychotics lessen the worsening of this response induced by NMDA receptor antagonists [51]. The Morris Water MAZE (MWM) assesses multiple cognitive functions, including learning, memory, and retention. The animal learns where a submerged platform is in a tank of water. Then the platform is moved or removed from the tank. PCP negatively affects performance on this test, and it is reversed by SGAs. Social interaction is assessed by placing unfamiliar rodents in a

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lighted arena, and then the amount of time they spend interacting is measured. PCP impairs their social interaction [52]. Animal models for anxiety disorders – Anxiety disorders are complex, and no one animal model is appropriate for all anxiety disorders. Anxiety animal models can be divided into two groups. Conditional response models, such as the Geller-­ Seifter conflict model, involve the animal’s response to painful or stressful stimuli. Unconditioned response models, such as the elevated plus maze model, involve the animal’s natural response to stimuli that do not involve stress or pain [10]. Animal models for potential anxiolytic effect are limited by being based upon suppression of normal behavioral response rather than on decreasing pathological anxiety [39]. Animal models for depression – The forced swim test is a highly predictive animal model used to screen for antidepressant effect. The rat is placed in a vat of water and forced to swim to stay alive. Eventually, the rat will cease to swim and will only move enough to keep its head above water. This is commonly referred to as a “state of despair,” but may more accurately be a learned adaptation [39]. Over the past 50 years, new psychotropics have primarily differed clinically by having different side effect profiles than older medications. In particular, SSRIs and other newer antidepressants are much less toxic in overdose situations than the tricyclic antidepressants. Clozapine is the one major exception, and it is unclear why clozapine reduces psychotic symptoms in many patients with schizophrenia who have not responded with other antipsychotics. If we want psychotropic drug development to produce more effective agents, it is critical that we have a better understanding of the basic neurological (as well as other systems) mechanisms underlying different human mental disorders. If successful, mental disorders could be classified based upon pathophysiology rather than symptom presentation [39]. New approaches may assist in our understanding of the pathophysiology of mental disorders and the development of future medications. Behavioral assessments that target a single neural circuit in both humans and other animals increase the utility of animal models. For example, stop signal reaction time has been used in both rodents and humans to demonstrate the effects of atomoxetine on decreasing impulsivity, and this is associated with activation of homologous areas of the inferior frontal cortex [73]. Thus, it is important to utilize animal behavioral models that have a human behavioral or cognitive counterpart. It has also been suggested that objective behavioral assessments should be incorporated into Phase II and III trials because they reflect the pharmacology of the drug and not just its effect on clinical symptoms [73]. Optogenetics can be used to visualize a genetically targeted neural circuit. This allows one to turn a neural circuit on or off. Artificial intelligence may also hold promise in being able to identify new biological targets and compounds for investigation [39]. The future may lie in the use of induced pluripotent stem cells (iPS cells) from patients with the disease of interest. These can be reprogrammed into almost any cell line and allow for the study of individual neurons with the same genetics as the patient. These can be further developed into cerebral organoids that resemble the developing human brain [65]. Patient-specific iPS cells can be

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transplanted into rodent brains. In a schizophrenia model, human glial cells produced from iPS cells are transplanted into mice producing an animal where the majority of the glial cells are human. The chimeric mice develop decreased social interaction, anxiety, and decreased prepulse inhibition. This has potential for producing animal models to study drug action. Advances in our ability to study brain function and evaluate behavioral and cognitive function may lead to advances in our understanding of mental disorders as well as their treatment. This could potentially result in patient specific drug development. However, the cost of this would likely be prohibitive.

5.2.5 Mutagenicity One of the nonclinical safety tests that must be performed prior to a new drug candidate’s approval is assessing the drug’s ability to cause changes to a cell’s DNA sequence or mutagenicity [31]. These changes have been linked to a drug product’s potential to cause cancer. These tests are performed using bacteria as well as mammalian cells and animals. The inactive ingredients in a formulation may also generate impurities as by-products of manufacturing or degradation during storage. This has led to the development of computer models based on chemical structure to aid in predicting the mutagenicity of both drug impurities and drug substance. These statistically-based Quantitative Structure-Activity Relationship correlations, or QSAR models, have been the subject of vigorous research by the FDA for predicting mutagenicity as well as other drug toxicities. There are now international guideliens [46] ratified by FDA and regulatory counterparts, that allow QSAR models to substitute for traditional laboratory tests for determining mutagenic of drug impurities.

5.2.6 Toxicology Considerations Animal models are used in preclinical drug development to simulate what occurs in human biologic systems and evaluate endpoints of interest. Selecting the most appropriate animal models for conducting the formal Good Laboratory Practices (GLP) toxicology studies is critical for predicting human toxicity. While animal models are rarely 100 percent predictive, those that are physiologically similar to the endpoint of interest can guide researchers as long as there is a grasp of the similarities and variances of the model as it relates to humans. Dose escalation studies can be used to explore the drug’s toxicology. Specific negative effects on major organ systems (e.g., brain, heart, kidney, liver) can be examined at each dose. In addition, the lethal dose in 50% of the animals studied (LD50) can be determined. Toxicology studies are typically conducted in rodents

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(mice or rats) plus one other species (e.g., dogs, minipigs, primates, rabbits). Even when testing in multiple species, human organ toxicity can occur in the absence of toxicity in other species. [60]. Establishing the safety of lead products is a culminating activity of the preclinical phase. The toxicology studies – also referred to as safety assessment – represent a pivotal component of the information that undergoes regulatory review and leads to the FDA’s go/no go decision for allowing a product to move forward into human clinical trials. Using appropriate animal models and methods for generating robust, reliable data will establish a toxicology profile for new drug candidates.

5.2.7 Regulatory Pathway: Preclinical to Clinical Trials New drug development is a highly regulated, complicated process that requires specialists and intense research and development skill sets in the medical research community. All regulations and safety indications must be observed carefully, and human and animal clinical trial subjects treated professionally and with the utmost care. The FDA’s [33] evaluates new drugs before they are approved to be marketed and sold. The regulations that CDER enforces work to ensure that drug products are safe and effective and that their benefits outweigh any known risks. The formal animal toxicity studies (preclinical) and the application to enter clinical trials are subject to FDA regulations: Good Laboratory Practices (GLP) and the  Investigational new Drug Application (IND) are discussed below. The toxicity studies intended to support applications for entering human clinical trials must be conducted under GLP. The GLP describes the FDA regulations for in vivo and in vitro experiments subject to FDA safety review. Investigational drugs being evaluated in nonclinical safety studies must comply with GLPs. The regulation embodies a set of principles that provides a framework within which laboratory studies are planned, performed, monitored, reported, and archived, covering the personnel, facilities, operations, and records that are involved in GLP studies. GLPs are designed to provide regulatory guidance for ensuring the integrity of data from nonclinical studies. In the USA, the GLPs are administered by the FDA and are found in the Code of Federal Regulations [15]. These regulations cover the definitive preclinical studies that FDA reviews prior to making the final decision regarding approval to start testing in humans.

5.2.8 Investigational New Drug (IND) Application Preclinical data are used as a basis to design the pivotal safety studies that will be included in the IND submission that is reviewed by CDER. As a new product undergoes preclinical evaluation, the sponsoring company collects data from a variety of

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prescribed testing to demonstrate that the drug is safe and effective for its intended use. Prior to being tested on people, laboratory and animal testing is conducted to determine how the drug works, whether it is successfully treating the targeted disease, and if it appears to be safe. Sponsors are required to submit an IND application to FDA prior to initiating clinical research. The IND must include animal study data and toxicity data, manufacturing information, clinical protocols, data from any prior human research, and information about the investigator. The FDA has 30 days to review the original IND submission. Clinical trials are allowed to proceed once the IND is approved by FDA. The FDA may decide a clinical hold to delay or stop the investigation if it is believed that participants are exposed to unreasonable or significant risks, investigators are not qualified, materials for the volunteer participants are misleading, or the application does not include sufficient information about the trial’s risks. The formal regulations that pertain to INDs can be found in Section 21 of the Code of Federal Regulations [15]. There are several parts referring to INDs, including the following: drug labeling, orphan drugs, protection of human subjects, financial disclosure by clinical investigators, IRBs, and GLPs for nonclinical lab animal studies.

5.3 Clinical Development Phase Once FDA approves the IND, a drug candidate can move forward to human clinical trials. CDER oversees the clinical trials necessary for the FDA to determine whether a new medication will be approved for use. The ultimate goal is to determine the efficacy, safety and quality of drug candidates and ensure the right dose and dosing schedule for a specified patient population. Other desirable properties of drug therapies include good bioavailability with low variability, distribution to the site(s) of action, limited metabolism, and a broad therapeutic index. The sponsoring company may conduct the early studies with clinical research companies or academic institutions with dedicated facilities for the conduct of early phase research until they reach the later phase larger clinical trials. Pharmaceutical companies often contract with Contract Research Organizations (CROs) to conduct and oversee their clinical trials. The CROs contract with private research clinics, academic research centers, physician groups, and hospitals to conduct the studies in order to enroll the number of patients required. The CROs provide oversite and monitor the sites to assure that they are completing research documentation in an appropriate manner. In this phase, regulatory compliance and oversight is in place and the clinical trials must comply with FDA Good Clinical Practices (GCP) [34]. These regulations are designed to ensure the integrity of clinical data and protect the rights, safety, and welfare of human subjects. There are three phases of clinical trials, typically starting with a small group of healthy volunteers (Phase I) to determine the safety and basic pharmacokinetics of the test product, to large studies involving hundreds to over one thousand patients at

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multiple study sites (Phase III). In order to progress from one phase to the next, the FDA must review the data and decide whether to allow the studies to progress to the next phase. This is considered “IND maintenance.” Clinical trials are designed to establish the efficacy and safety of investigational drug products and to answer other questions about the agent as needed. Protocols are developed that explain what will occur in the trial, how it will be conducted, and why each step is necessary for answering scientific questions about the product as well as safeguarding the health of participants. The trials must follow the study plan that is developed by the researcher or manufacturer and approved by the FDA. Trial participants must meet the eligibility criteria defined in the protocol in order to qualify, and the plan stipulates how many people will participate in the study and how long it will last. The research questions and objectives will dictate whether the trial will include a control group, how the drug will be administered, what dose(s) will be studied, as well as how the data will be reviewed and analyzed.

5.3.1 Phase I Clinical Trials Traditionally, Phase I psychotropic clinical trials have focused on pharmacokinetics (PK), safety, tolerability, and definition of the maximum tolerated dose. The PK profile is impacted by the drug’s physicochemical properties, formulation, and route of administration. In addition, extrinsic factors including diseases, other medications, and food can impact the PK profile, and traditionally only healthy male volunteers have been included as research subjects in psychotropic Phase I trials. The clinical pharmacology information from Phase 1 informs the design of Phase II and III trials. More recently, individuals with the disease state of interest are being incorporated into Phase I studies. For example, it is known that individuals with schizophrenia tolerate D2/D3 antagonists better than healthy individuals. Studying subjects with the target illness in Phase I studies may better predict the dosages to be used in Phase II trials [23]. In addition, psychotropics have significant adverse effects, and medications with the potential for use in difficult-to-treat mental illnesses may have Phase I trials conducted in the population that would receive the medication. An example is clozapine. After clozapine was found to cause agranulocytosis, its bioavailability study for the NDA for use in treatment-resistant schizophrenia was shifted to be conducted in males with treatment resistant schizophrenia [13]. Phase I studies may be either open label or randomized, placebo-controlled, double-blind trials, escalating single and multiple-dose studies in a small number (12 to 100) of healthy volunteers. There may be two phases to these studies: a single ascending dose (SAD) phase and a multiple ascending dose (MAD) phase; the SAD phase is conducted first, followed by the MAD phase. There has been increasing interest in collecting pharmacodynamic data as part of Phase 1 trials with the hope of informing the design of Phase II trials, particularly as it relates to dose. Increasingly, potential biomarkers are being introduced into

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early clinical trials. In order to be useful as an outcomes measure in clinical trials, the biomarker needs to confirm the diagnosis or predict response to treatment. For example, it has been suggested to perform targeted neuroimaging and collection of potential biomarkers during Phase I [56]. The effects of drugs on neural circuits can be studied using such techniques as function magnetic resonance imaging 9fMRI) and high-density electroencephalography [37]. The use of cognitive challenges during fMRI in individuals with schizophrenia may allow for the identification of medications with pro-cognitive effects. Mismatch negativity (MMN) has been described as possessing nearly all of the features of a translational research biomarker. It is a neurophysiological response usually measured by auditory evoked potentials that involve assessing the effects of an uncommon stimulus that follows repeated normal stimuli. It is impaired in schizophrenia and involves both dysfunction in neural circuits and clinical outcome. Dysfunction in schizophrenia involves impairment in both auditory sensory perception and cognition. It can be used in both rodents and humans, and NMDA receptor antagonists such as ketamine or phencyclidine negatively affect it in both preclinical and clinical models. Both glycine and the glycine agonist d-serine reverse the negative effects of ketamine on auditory evoked potential [8]. In perhaps the best example of the use of a biomarker in antidepressant studies, the effects of deep learning on the fMRI was associated with an R2 of 0.48 on predicting Hamilton Depression Rating Scale (HAMD) improvement with a number needed to treat (NTT) of 4.86 patients [57]. It has also been suggested that the use of fMRI during Phase I trials could actually decrease the overall cost of drug development. Another example is the use of positron emission tomography (PET) to study molecular interactions and potentially determine the dosages associated with efficacy or adverse effects. Currently marketed antidepressants cause neurogenesis in the hippocampus. MRI measured changes in hippocampal volume have been proposed as a screen for potential antidepressant effect. If increases in hippocampal volume predict antidepressant activity, this could be used to explore the potential of compounds not acting on monoamine receptors as antidepressants. This technique is also appealing because it can be used in both humans and nonhuman species. Although this has been explored in a Phase 1b clinical trial, it is too early to confirm its predictability [25]. Thus, the use of multiple pharmacodynamic measures during Phase I studies may help identify unique mechanisms and the clinical profile as well as to better predict the dosages to use in Phase II trials, and perhaps even efficacy [23]. However, there is a need for harmonization and standardization of the methods used. If biomarkers that predict a drug’s efficacy can be developed, these could be used in Phase I clinical trials in patients with the disease of interest. If no positive effect on the biomarker is found, then costly Phase II and Phase III clinical trials could be avoided. Although not yet definitive, brain-derived neurotrophic factor (BDNF) is potentially such a biomarker for antidepressant activity [73]. Increased use of Model Informed Drug Development (MIDD) is guiding clinical trial development, optimizing dosing, and providing supportive evidence for

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efficacy and in policy development. The use of modeling has the potential to speed up the development process and increase efficiency of conducting clinical trials to support drug approval. Extrapolation of efficacy and safety from small data sets in difficult-­to-study populations (children, rare diseases, hepatic dysfunction, drug interactions etc.) and making model-based inferences in lieu of pivotal clinical data to make efficacy, dosing, and safety recommendations are two high impact areas for use of modeling in drug development. Population pharmacokinetic computer modeling (in silico) in CNS drug development is increasingly being used, especially in the area of dose formulation [43, 75]. The FDA and EMA have developed several guidance documents for modeling in the drug approval process. [24, 26, 36, 67]. The importance of early pharmacodynamic studies is clearly recognized. Assessing “pharmacodynamic target-based measures” early in clinical research may not only help dose response relationships to be used in Phase II and III trials; it potentially helps better define mechanism of action. The NIMH through its contracting process has created research teams comprised of pharma researchers, academics, and NIMH researchers to support early pharmacodynamic assessment of candidate agents [41]. FDA reviews the Phase I data and if they find sufficient evidence to support continuing clinical trials, the drug candidate is allowed to move into Phase II. Phase I studies typically last several months, and 70% of drugs move to the next clinical phase [29].

5.3.2 Phase II Clinical Trials Phase II studies focus on the drug’s efficacy and adverse effects. They can last from several months to 2 years in duration. Phase II trials involve testing the experimental drug on a larger number (up to several hundred) patients who have the disease of interest. Phase II trials are dose finding studies looking for the appropriate doses for evaluating safety and efficacy in larger Phase III trials. These trials generally include a study arm which uses up to the maximum tolerated dose (MTD) from the Phase I trials. Because of the small number of subjects in Phase I, the dose may need to be adjusted either down if excessive toxicity is observed or increased if the desired biological effect is not seen. Early Phase II trials are often open label, but randomized placebo-controlled trials are required by the FDA to demonstrate efficacy. Because of the large placebo response rates seen in most studies of mental disorders, a placebo group must be included to prove efficacy. The FDA does not allow the use of standardized treatment comparison studies (i.e., noninferiority trials) without a placebo group [29]. It is critical that a priori sample sizes be calculated to assure that adequate number of subjects are enrolled to be able to show a statistical difference between groups. Conventionally, an α ≤ 0.05 is used to demonstrate a difference between groups. Although β may vary, it is typically β ≤ 0.2.

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It is essential to assure that patients enrolled into clinical trials have the disorder of interest, and the Structured Clinical Interview for DSM (SCID) or MINI International Neuropsychiatric Interview (MINI) are generally required to verify the patient’s diagnosis. In general, patients with varying duration of illness or numbers of episodes are included in Phase II and III trials. However, if an indication for a treatment resistant disorder is being sought, then the patient subject population must reflect the intended indication. In some cases, an indication as an adjunctive agent is being sought, then the patient population would be comprised of individuals who failed to obtain adequate response with a standard treatment, and patients are randomized to receive either the investigational drug or placebo plus the standard treatment. Psychiatric diagnoses are based on a clinical syndrome which is represented by a set of symptoms or behaviors, severity of symptoms, duration of symptoms, impairment in psychosocial functioning, and other clinical characteristics. Symptom overlap occurs from syndrome to syndrome (e.g., anxiety is often present in depression, bipolar disorder, and schizophrenia, as well as in anxiety disorders). Because of the spectrum of symptoms and the overlap, it is challenging to tie any one syndrome to a specific neural circuit. However, it is often possible to tie one specific symptom to a given neurocircuit, and with the correct biomarkers, perhaps to a specific dysfunction in that circuit. Preskorn argues that clinical drug trials should be based upon treating specific symptoms that are associated with dysfunction in a specific neural circuit [64]. Research Domain Criteria (RDoc), established by the NIMH, is an attempt to integrate scientific data with clinical phenomena. This transdiagnostic approach incorporates such data as biomarkers, genetics, neurocircuitry, imagining, and neuropsychology with five domains of human emotion and behavior [21, 64]. Human behavior is divided into five categories based upon positive or negative valence. This has been referred to as a “systems neuroscience approach” to drug development with the goal of understanding the basic neuroscience associated with human behavior [73]. Collection and compilation of these types of data into large datasets may allow for computational modeling of future new medication [21]. Approximately 33% of drug candidates in Phase II trials move into Phase III studies [29]. Use of a different approach to elucidating the clinical effects of potential drug therapies has the potential to improve the percentage of drugs moving into Phase III testing.

5.3.3 Phase III Clinical Trials Following FDA review and approval of Phase II trial data, sponsors are allowed to continue into Phase III clinical trials. Study participants who have the disease or condition are enrolled and can involve hundreds to a few thousand volunteers. A priori power analysis calculations are performed in order to determine the number of research subjects that must be enrolled in order to evaluate efficacy. However, much larger numbers of individuals treated with the investigational drug are needed

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to determine safety. These studies focus on efficacy and monitoring of adverse reactions, dose-response, wider populations, efficacy at various stages of disease, and use in combination with other agents. These large and extensive trials take significant time and are expensive. Increasingly, quality of life and social functioning assessments are being incorporated into Phase III trials. In the USA, Phase III trials are double-blind and typically placebo-controlled. This helps to eliminate bias when interpreting results. Patients enrolled in Phase III trials are typically between 18 and 64 years of age, do not have a history of nonresponse to psychotropic treatment, have no serious general medical disorders and no co-occurring mental disorders, including alcohol or substance abuse. This “clean” clinical trial patient population is different than that often seen by clinicians in practice, and thus, generalizability of clinical trial results can be limited [51]. Phase III trials are the final clinical phase of test before the drug product’s details and clinical trial results are submitted to the FDA for consideration of approval. They generate important data that reflect the test product’s efficacy and adverse reactions. In general, the FDA requires two placebo-controlled, randomized clinical trials indicating that the psychotropic medication is efficacious and safe. If the medication is already FDA approved for use in adults, then only one efficacy and safety trial is required for the same indication in children or adolescents. There are exceptions to the use of the investigational drug compared with only a placebo control group. For example, in the esketamine clinical trials, patients were randomized to receive either esketamine or placebo added to a newly started antidepressant [40]. In Kane’s classic study of clozapine in treatment-resistant schizophrenia, chlorpromazine plus benztropine was used as the control [50]. In addition to large randomized placebo-controlled trials to demonstrate efficacy, tolerability, and safety in treating the acute phase of a mental disorder, the FDA requires continuation studies. Since most mental disorders are either chronic (e.g., schizophrenia) or recurring (e.g., major depressive disorder [MDD]), continuation trials must be of sufficient duration for the specific disorder to demonstrate that the drug has continued efficacy and that it is safe and well tolerated. The design of such trials is variable. They may enroll drug responders, and then after the designated continuation phase, patients may be randomized to continue on the investigational agent or receive placebo. This allows comparison of relapse rates following discontinuation [29]. These studies may be performed in either Phase III or IV. In general, the FDA has required efficacy of psychotropics to be demonstrated by two independent clinical measures, typically both a validated rating scale for the disorder [e.g., Positive and Negative Symptom Scale (PANSS) for schizophrenia and the HAMD for MDD] and a clinical global impression (CGI) scale. The CGI-­ Severity (CGI-S) is preferred because it is subject to less recall bias than the CGI-­ Improvement (CGI-I) [29]. Although multiple measures of clinical outcome may be used in a clinical trial, it is critical that the primary measures of efficacy be determined when the trial is designed, or in an a priori fashion. Primary outcomes must show statistical significance (typically α  ≤  0.05), between active compound and placebo to demonstrate efficacy of the test drug. Efficacy cannot be determined

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based upon statistically significant improvements in secondary measures if a statistically significant difference is not found in the primary outcome measure. Although there is great interest in biomarkers, no universally accepted biomarkers for drug efficacy in mental disorders currently exist. For example, in Alzheimer’s dementia, which is often considered both a neurological and a psychiatric disorder, Β-amyloid plaques are associated with both the diagnosis and the severity of Alzheimer’s dementia. Several anti-β-amyloid monoclonal antibodies have been developed that decrease β-amyloid plaques in the brain, but they have not been shown to improve clinical symptoms or slow clinical deterioration. The Food and Drug Administration’s (FDA’s) approval of aducanumab is an example of a drug that produced great controversy regarding the use of a biomarker to demonstrate efficacy in Alzheimer’s disease. In clinical trials, aducanumab decreased Β-amyloid plaques in the brains of patients with Alzheimer’s, but it did not consistently improve clinical symptoms or delay cognitive decline compared with placebo [66]. It could be useful to utilize biomarkers to exclude patients from clinical trials who are unlikely to respond to treatment. For example, elevated baseline C-reactive protein (CRP) (> 1  mg/L), a marker of inflammation, has been shown to predict poor response to SSRIs in females, but not in males. It could be useful to use this as a biomarker to exclude women with depression from clinical trials with serotonergic antidepressants. It also appears that patients with elevated CRP serum concentrations respond better with noradrenergic and dopaminergic antidepressants [48, 49]. Challenges exist with the use of rating scales to evaluate efficacy in clinical trials. The total score is the sum of the severity ratings on individual items. The data are not continuous, and ideally, should not be evaluated using parametric statistics. There is not necessarily a linear relationship between change in the total score and the actual clinical status of the patient. For example, depending on the severity of the individual items, a patient with schizophrenia and a PANSS score of 48 could actually be just as or more psychotic than a patient with a PANSS score of 90 [64]. Adaptive design trials have been recommended as one way of improving the demonstration of efficacy. In adaptive designs, prospectively planned interim analyses are performed and the trial adapted without damaging the scientific integrity of the study [56, 69]. This can allow for enrichment of treatment responsive patient populations and may actually decrease the enrollment requirements and allow an earlier decision to be made about success or failure [69]. Placebo response is a huge challenge in clinical psychopharmacology. Placebo response has increased over the past 40–50 years, and in some studies 50% or more of patients have experienced clinically significant improvement with placebo. High placebo response rates can make it challenging to distinguish active medication from placebo. Several reasons have been proposed for the increase in placebo response including: the move by the industry to conduct clinical trials in private clinics rather than academic settings, varying research experience of clinical investigators, the rise of professional subjects who repeatedly enroll in clinical trials, variable intra-rater and inter-rater reliability in performing psychometric assessments, and lack of rigor of clinical investigators in adhering to study enrollment

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criteria [51, 56]. In addition, the amount of time that clinical investigators and their staff spend with clinical research subjects at frequent visits potentially serves as a form of supportive psychotherapy. Although it is important to collect appropriate data for efficacy and safety purposes, perhaps data collection should be streamlined in order to shorten the visits. A placebo run-in period, with placebo responders eliminated before randomization, has been frequently used in attempt to decrease placebo response rates. However, a recent large meta-analysis of antidepressant clinical trials found that the use of a placebo run-in did not alter the difference between active drug and placebo response rates [68]. Approximately 25–30% of drugs complete Phase 3 trials and move forward to be considered by the FDA for marketing approval and continuation to Phase IV studies.

5.3.4 Pediatric Considerations Additional considerations must be given when conducting clinical trials of psychotropic medications in children or adolescents. Obviously, the agent must be used in clinical trials for a mental disorder seen in pediatric populations. A valid scientific rationale must exist for studying the agent in children and the possibility of different pharmacodynamics and pharmacokinetics must be considered. Both physiological and emotional development are dynamic processes, and potential differences in efficacy and tolerability must be studied for each age group to be included in the FDA product labeling. Juvenile animal studies may also be needed to examine the effects of the agent on growth and development [29]. Medications may have developmentally dependent adverse effects that are different than those seen in adults, and it is important that this be systematically assessed. Currently, no standardized assessments for adverse events in children are required [14]. The three approaches to soliciting adverse effects are general inquiry, checklist of adverse effects previously reported with this drug class, and a systematic potential adverse effects checklist of a review of systems [14]. The limitations of not using a standardized approach to safety assessment challenge became readily apparent in the FDA’s assessment of potential suicidality of antidepressants in children and adolescents [63]. Although there is a suicidality item on most depression rating scales, suicidality in antidepressant trials had been primarily assessed by general inquiry. This would result in the clinical investigator recording a narrative note regarding reports of suicidal ideation or attempt. When the FDA saw a potential signal of suicidality in antidepressant trials in children and adolescents, they contracted with an independent group of suicidality experts to blindly evaluate the case reports. They developed a standardized assessment of the case reports, the Columbia Classification Algorithm of Suicide Assessment (C-CASA). After blindly reviewing the case reports, the panel found that the pharmaceutical companies tended to over identify cases as suicide attempts and under identify overall suicidality. This led the FDA to require the use of the C-CASA in evaluating case reports of possible suicidality [63]. In addition, the FDA recommends the prospective use of the

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Columbia Suicide Severity Rating Scale (CSSRS) in clinical trials of antidepressants [62, 63]. The clinical failure rate of psychotropic medication is higher in children and adolescents than in adults. There are likely multiple reasons for this. Youth studies share the challenges of high placebo response rates and the limitations of symptom-­ based assessments of efficacy which are also a bane for psychotropic studies in adults. Placebo response may be larger in children because of parent or other caregiver’s expectations for improvement. Children and adolescents tend to have significant state dependency with regard to symptoms such as depression and anxiety, and thus, spontaneous improvement may occur depending on the youth’s environmental situation. Studies in children and adolescents commonly include a broad age range. CNS as well as other organ development is a dynamic process throughout childhood, and including broad age ranges introduces greater heterogeneity into the subject population. The sample sizes in these studies are typically too small to perform subgroup analyses [40].

5.4 Regulatory Review Process The FDA ensures that US consumers have access to safe medicines and treatments. The FDA’s CDER evaluates new drugs before they are approved to be marketed and sold [33]. The regulations that CDER enforces ensure that drug products are safe and effective and that their benefits outweigh any known risks. There are mechanisms in place, including labeling, dosing directions, patient package inserts, and other education materials, to ensure that healthcare professionals and patients have the information they need to use medicines appropriately. CDER teams composed of clinicians, chemists, statisticians, pharmacologists, and other scientists to review the sponsor’s submitted data and make the determination whether there is sufficient proof that the drug should be allowed to move into the next phase in the pathway. These are scientific, unbiased, independent reviews by CDER teams – they review data to assess whether there is sufficient evidence to either approve or reject the company’s application to approve a new drug product. The FDA commonly issues guidance documents to assist sponsors in designing studies that are appropriate for NDA submission. However, these guidance documents often lag behind advances in research in the discipline. For example, the last FDA-approved guidance document for the development of drugs for MDD was approved in 1977. A draft of a revised guidance document for MDD was released for comment in 2018, and it had yet to be approved by submission of this chapter [30]. Because of the pharmaceutical industry’s reluctance to perform studies in children, the Congress passed two important pieces of legislation  – the Best Pharmaceuticals for Children Act (BPCA) and the Pediatric Research Equity Act (PREA). PREA requires the industry to perform efficacy and safety studies of

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certain drug categories in children if the product has the potential to be beneficial for children with the given disorder. The BPCA grants the company an additional 6 months of patent protection if the company conducts studies in children. It is noteworthy that the BPCA also provides the NIH with funds to study drugs FDA approved for use in adults if the medication would be potentially beneficial for children and adolescents [40].

5.4.1 Regulatory Pathway: Clinical Trials to Commercialization A new drug application (NDA) can be filed with the FDA for review and approval following completion of clinical trials. Throughout the development pathway, efforts to scale up production of the active therapeutic ingredient (ATI) and the final formulation are occurring. During every development phase, sponsors collect information and data to include in the NDA. These data will need to be sufficient and compelling so that FDA reviewers can determine whether the drug’s safety, efficacy, labeling, and manufacturing align with FDA’s goal of approving products that meet strict criteria and whose benefits outweigh their risks, ultimately ensuring product quality and integrity. The NDA document presents a story of the drug’s development, from the ingredients in the dosage form to the results of animal testing and stability studies, including results from clinical trials, profiles of drug absorption, distribution, and metabolism, and pharmacodynamics, toxicology, manufacturing and packaging processes, and labeling requirements. The timeline for reviewing NDAs has been significantly decreased in the past 20 years. The median FDA review and approval times have decreased from 20.9 months and 26.9 months in 1993 to 10.1 months and 10.1 months in 2016 [27].

5.4.2 NDA Review and Approval The first step in the NDA approval process is for the FDA review team to determine whether the application is complete. If it fails to meet this standard, the review team can refuse to file the NDA.  For complete NDA’s, the team has 6–10  months to decide if the application meets the standards for approval. In addition to reviewing the various sections, FDA inspectors visit clinical sites to ensure there is no evidence of fabrication, manipulation, or withholding of data. The various reviews and other documents are consolidated into an action package or the formal record of the FDA review.

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For drug products shown to be safe and effective for their intended use, the FDA will work with the sponsor company to develop and refine the prescribing,or labeling information. Labeling is a prominent feature that must accurately and objectively describe the basis for approval and the best use for the drug. It is common for an application to have issues, both major and minor, that need to be resolved prior to approving a drug for marketing. These can range from questions pertaining to existing data to the FDA requiring additional studies. It is up to the sponsor company to decide whether they want to continue development of the product.

5.4.3 Abbreviated NDAs The Drug Price Competition and Patent Term Restoration Act of 1984, also known as Hatch-Waxman, established the approval pathway for generic drug products and provisions that involve patents and exclusivities related to new drug applications. The approval of generic drug products requires submission of an Abbreviated New Drug Application (ANDA) [32]. These are considered abbreviated since generic drug approvals generally require limited preclinical and clinical data to establish safety and efficacy since they are allowed to refer to the innovator company’s data that were submitted in the original NDA. Generic applications must scientifically perform in the same way as the innovator company’s drug product. This can be accomplished using in vitro and human in vivo testing to prove that there is bioequivalence – the same rate and extent of absorption, distribution, metabolism, and excretion – when compared with the innovator product. The FDA has an additional “hybrid” or “bridge” pathway called the 505(b)(2) pathway, for new products that aren’t necessarily a copy of the originator product. Examples might include new formulations, new indications, new combinations, new route of administration, minor changes to the molecule such as prodrugs, etc. The application uses all of the safety and efficacy data from the originator product and creates a bridge between their new product and the original product.

5.4.4 Advisory Committees The FDA has established advisory committees to provide FDA with independent opinions and recommendations from outside experts on applications to market new drugs. These committees are composed of outside experts, who receive a summary of the information from the sponsor application and have access to the FDA’s review of the application documents. Advisory committees recommend approval or rejection of an NDA; however, FDA makes the final decision.

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5.4.5 Expedited Review Programs The FDA’s expedited review programs are intended to facilitate and expedite development and review of new drugs that address unmet medical needs in the treatment of a serious or life-threatening condition. The four programs are fast track designation, breakthrough therapy designation, accelerated approval, and priority review designation. The purpose of the expedited review guidance is to provide a single resource for information on the FDA’s policies and procedures for these four programs as well as threshold criteria generally applicable to concluding that a drug is a candidate for these expedited development and review programs. In particular, “breakthrough therapy” designation allows for more rigorous feedback and expedited review than earlier expedited review programs [11, 32, 37].

5.4.6 Prescription Drug Labeling Information FDA approves labeling information provided to patients in medication guides (MG), patient package inserts (PPI), and instructions for use (IFU). These are available for consumers and patients and include facts about adverse effects, drug interactions, proper storage, and other useful information. These various types of labeling information align with the FDA’s Risk Evaluation and Mitigation Strategy (REMS) drug safety program for medicines with serious safety concerns. REMS are created with the goal of ensuring proper use, monitoring, and safe use of medications. PPIs provide the information that is included in patient labeling, providing comprehensive and considerable detail about a drug product. These are developed by the manufacturer, approved by FDA, and required for specific products or classes of products. For other products, PPIs may be submitted to FDA on a voluntary basis by the manufacturer and approved; however, distribution is not mandated. MGs are primarily for outpatient prescription products with potential serious public health concerns and are provided to the patient when the product is dispensed. They are required if labeling could help prevent serious adverse events, enhance patient adherence to directions or affect a patient’s decision to use a product. IFUs are FDA approved labeling developed by the manufacturer that are dispensed with specified products with complicated dosing instructions. These are intended to help the patient properly use the product.

5.5 Phase IV Activities FDA oversight continues after a drug product is approved for marketing and is referred to as post-marketing surveillance. Following NDA approval, compliance with manufacturing and distribution of new drug products is closely monitored. During Phase IV,

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additional clinical trials may be required for observing long-term efficacy and ongoing monitoring of adverse effects and assessment of health outcomes.

5.5.1 Phase IV Clinical Trials Phase IV clinical trials may be required of the drug product sponsor as a condition for approving the marketing application. Pre-NDA clinical trials only monitor hundreds to a thousand or more patients while Phase IV trials monitor how a drug product performs in a broader population. These studies aim to assess the long-term risks and benefits, monitor known adverse effects, and identify any rare but serious adverse effects. The Phase IV trials can increase confidence in a product. However, in some instances, the product may be withdrawn from the market based on what is discovered when it is used in larger populations. Pharmaceutical companies may decide to perform comparative efficacy studies as part of Phase IV.  These may be noninferiority or superiority trials. These are often performed in hope of providing the company with a marketing advantage for the drug. The company may decide to pursue additional indications for the drug or obtain FDA approval for the use of the drug in other populations (e.g., children or adolescents), and this results in a return to Phase III trials.

5.5.2 Monitoring Adverse Effects The FDA has created a post marketing safety surveillance program for all marketed drug products. The regulations require manufacturers to report adverse events received from healthcare professionals and consumers for inclusion in the FDA Adverse Event Reporting System (FAERS). This allows the  FDA to identify and monitor new safety concerns, evaluate a manufacturers’ compliance with FAERS regulations, and provide information in response to outside requests. Additionally, voluntary reports can come directly from healthcare professionals and consumers. This database allows interested parties to find information regarding adverse events for drug products.

5.5.3 Phase IV Health Outcomes/Quality of Life Following the approval of a new drug product, the Phase IV trial data may also study other characteristics of the drug therapy, including the impact on a patient’s quality of life or the cost effectiveness of the treatment. These questions may take years to answer and are influenced by other factors including the quality of medical care, treatment outcomes, hospital readmissions, the patient experience, and mortality.

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5.6 Bioethical Issues Protection of human subjects should always be at the forefront of designing, implementing, and conducting clinical trials. The FDA [15] and the European Medicines Agency (EMA) have both promulgated rules around human subjects’ protection – most of which are very similar in nature and structure with key differences. The International Council for Harmonization of Technical Requirements for Pharmaceuticals for Human Use (ICH) has developed guidelines to help navigate these regulations commonly referred to as Good Clinical Practice [47]. Much of the regulations and guidance is derived from key foundational documents  – the Nuremberg Code [2], the Belmont report [72], and the updated report from the Declaration of Helsinki [76]. The FDA also has guidance for sponsors, investigators, and institutional review boards. [35]. Each of these outlines the necessary steps for assuring the rights and welfare of human subjects – including the review by institutional review boards, informed consent procedures, the processes involved to mitigate risks to subjects, and clinical trial design expectations with respect to assuring the quality of the work, the feasibility of the study, and the reliability of the results. Study design is a critical component to assuring the ethical construct of a clinical trial. That is, making sure the trial is designed to produce results that are meaningful and reliable and have utility. ICH has developed multiple guidelines for the design and conduct of clinical trials [45]. There is also the issue of people from racial and ethnic minorities being underrepresented in research. Diversity, which includes race, ethnicity, gender, socioeconomic status, age, and stage of disease, is essential to the clinical trial industry to improve the safety and efficacy of new treatments being developed and the generalizability of results. The lack of diversity in clinical trials is an obstacle to understanding the safety and efficacy of novel therapies across population subgroups, which is important for reducing disparities. Development of drugs for psychiatric conditions has all the same ethical challenges that developing drugs for other conditions would pose. Psychiatric drug development also presents some ethical challenges unique to the conduct of psychotropic clinical trials. Psychiatry and patients with mental illness are subject to higher degrees of stigma, and some individuals are critical of the very nature of the field, leading to a higher level of negative attention from many sources. Patients with mental illness are often perceived as being particularly vulnerable  – even to the point where even the notion of conducting trials in the population is questioned. Clearly, there is a need to better understand the biological and physiological underpinnings of psychiatric illnesses and develop a better taxonomy that would facilitate study of more homogeneous subpopulations of patients. At the forefront of ethical issues in psychiatry is the use of placebos versus active comparator study designs. The double-blind placebo controlled study design has long been considered the gold standard in creating evidence of efficacy in psychiatric clinical trials. Notably, the FDA still provides guidance that the use of placebos is one of the more certain strategies for showing efficacy of a new molecule. The

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EMA uses the Declaration of Helsinki as a guide for the drug development process. The Declaration of Helsinki is clear about the use of placebos in clinical trials: Use of Placebo “The benefits, risks, burdens and effectiveness of a new intervention must be tested against those of the best proven intervention(s), except in the following circumstances: [76] • Where no proven intervention exists, the use of placebo, or no intervention, is acceptable; or • Where for compelling and scientifically sound methodological reasons the use of any intervention less effective than the best proven one, the use of placebo, or no intervention is necessary to determine the efficacy or safety of an intervention and the patients who receive any intervention less effective than the best proven one, placebo, or no intervention will not be subject to additional risks of serious or irreversible harm as a result of not receiving the best proven intervention. • Extreme care must be taken to avoid abuse of this option.” The EMA by in large does not allow placebo-controlled research for psychotropic drug development. The divergence of guidance across the continents is challenging in psychiatry as it is difficult to satisfy both guidance documents when simultaneously developing a drug in Europe and the USA. Unfortunately, the solution is to conduct separate trials to meet the specifications, exposing greater numbers of subjects to potentially nontherapeutic and noxious agents, increasing the cost of drug development, and delaying the development of the products. The ethical issues surrounding the use/nonuse of placebos are multifaceted. On the surface, the concern would seem to be the use of placebos amounts to withholding treatment in patients with serious disorders for the duration of the trial. For psychiatric disorders, this increases the risk for symptom exacerbation and relapse with potential consequences of suicidal ideation/attempt, death by suicide, reincarceration, and a host of social/educational/employment consequences. Clearly placebos are unethical when the consequence of withholding standard treatment is lethal or has the potential to cause irreversible morbidity. Placebos are also considered ethical – as guided by the Declaration of Helsinki when there are no standard treatments and, in the situation where the experimental therapy is added to standard therapy. Exploring the issue further, one must ask – what are the alternative study designs to placebo-controlled studies and the ethical consequences of those alternatives? Active control studies would seem to be the logical alternative – comparing the test compound with currently available treatments. The challenge with this approach in psychiatry is the high rate of placebo response in clinical trials (30% or greater), resulting in a high number of failed studies. The results of active control studies would be challenged on the basis of the reliability of the results and risks approving a therapy that might in actuality be no better than placebo. For example, if a comparator study showed an investigational drug to be equally effective as diazepam in generalized anxiety disorder, one would conclude that the investigational drug is effective. However, if a placebo group was included in this study, and placebo

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response was equivalent to the investigational drug and diazepam, then it is a failed study. If a study design produces unreliable results – then the ethics of enrolling subjects into the study comes into question. Furthermore, the active control design would need to use a superiority analysis design – the test compound would need to be better than the standard. Superiority is a high hill to climb in developing drugs for psychiatric conditions that are highly variable along many constructs. Most new agents to market are no more efficacious than existing therapies. Noninferiority analysis, where the test compound is compared to a standard treatment, is another design to be considered. The question that arises with these analyses is whether the endpoint of noninferiority has any clinical utility – again bringing to question the ethics of enrolling subjects in such a study. Additionally, noninferiority studies often need to have significantly more subjects enrolled in the trial, potentially increasing the exposure to a test product that could have serious adverse effects or may not be efficacious. Clearly there are good arguments on both sides of the placebo/antiplacebo debate. At this point, the FDA continues to press for “adequate and well-controlled” studies to demonstrate the effectiveness prior to approval. It is likely we will continue to see a mix of randomized placebo-controlled trials (RPCT) and other designs used to meet this standard. When placebos are utilized in a trial, Miller offers four ethical considerations for design and implementation [12, 55]: 1. Placebo-controlled trials must be scientifically sound and the results of the study have potential significant clinical utility. 2. Risks should be minimized and justified relative to the anticipated benefits to clinical care and individual subjects – subject selection should consider risks and benefits to the individual; there should be a plan for managing distress associated with temporary exacerbations and removal of the subject from the trial if severe. Monitoring/assessment should target known risks such as suicidal ideation, and duration of exposure to placebo should be as short as possible. 3. Subjects must give adequate informed consent – free from coercion, with clear delineation that it is research and not treatment, the chances of receiving placebo are understood, and individual vulnerabilities are attended to. 4. Subjects should be offered short-term individualized treatment after completion of research participation to maintain their symptom stabilization and be referred for continuation of care Another key challenge to clinical trial work in the psychiatric population is the perception that patients are a vulnerable population and therefore must receive higher levels of protection. Vulnerability within the population of people with mental health disorders can be grouped in to two major categories  – capacity-based vulnerability and power-based vulnerability. Capacity-based vulnerability refers to the inability to make an informed consent decision based on the subject’s impaired capacity. Power-based vulnerability refers to the power differential between the subject and the subject’s provider/investigator. There also exists a wide range of vulnerability within this population and not all subjects are considered vulnerable. For example, studies in depression found that 90% of subjects had full

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comprehension and that the levels of comprehension were similar to patients from the general community [4, 70]. Clearly there are subgroups within the population that are more at risk for capacity-based vulnerability that need to be identified [78]. The ability to provide voluntary consent often comes into question in trials of psychiatric conditions. Much has been written about the decisional capacity of psychiatric patients in clinical trials. The four key principles of decisional capacity with respect to providing informed consent are understanding  – ability to know the meaning of information, appreciation – relating the information to oneself, reasoning – using information to weigh the options, and expressing a clear choice – making a clear decision [5, 42]. There are many different approaches to assessing capacity. The use of the MacArthur Competence Assessment Tools for Clinical Research and for Treatment (MacCAT) is an assessment tool with good empirical data to support use in populations of subjects where the subjects’ ability to understand, appreciate, reason, and express a choice are questioned. The MacCAT has been utilized in the consent process to verify decisional capacity [22] L). Additionally, there are considerations, again not unique to psychiatry, surrounding the use of a legal guardian, spouse, parent, or other surrogate to make decisions for the subject who may not be capable of deciding about trial participation. Including patients in clinical trials that are involuntarily detained is a relatively unique challenge in psychiatry. These are patients admitted to a psychiatric facility under the provision of civil involuntary detention laws – where a clinician and judge are making decisions about treatment. States and local treatment culture vary in how to handle cases where the patient qualifies for enrolling in a clinical trial but is involuntarily detained. The willingness of guardians to allow their wards to participate in clinical trials also varies. Public administrator guardians may be less likely to agree to participation – especially in higher risk studies – and often request judicial review prior to signing the consent form. Family member guardians may also be more protective of their loved one. Interestingly, family members may also be more likely to agree to allow participation under the notion that they are helping the patient find a better treatment – especially if the patient has had difficulty managing symptoms. In any case, there should be an agreement by the subject to participate (assent) if a surrogate is providing consent. Research subjects and guardians may have higher than reasonable hopes that participation in the clinical trial will provide benefit – so called therapeutic misconception. These misconceptions where the subjects fail to appreciate the differentiation between the requirements and obligations of clinical research and treatment as usual can undermine the potential for the subject to provide a true informed consent. The perceived benefit can come in many forms – increased attention or potential for improvement in long-standing symptoms. In the minds of patients, these may be prioritized over the weighing of potential risks, disadvantages and incumbrances associated with the study procedures. The therapeutic alliance a provider has with the patient is an important bias that has the potential to increase this misconception as patients may be more likely to follow the recommendation of their provider and the provider, out of an obligation to do what’s best for the patient, may be more likely to refer to a clinical trial if it appears to offer a benefit that cannot be currently

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provided [6]. Clinical trials designed with randomization, and which use strong informed consent processes that do not involve the provider as the one explaining the study, that make a clear distinction between the objectives of the research, and which acknowledge that research by definition has inherent risks and may not result in the patient deriving any benefit from the study are the ones more likely to be perceived as being ethically designed and implemented. Potential therapeutic benefit to the patient is a secondary issue to consider and discuss with the subject [12]. Another challenge in designing clinical trials is creating a set of experiments that answers pressing clinical issues and the results of which are translatable to clinical practice. Few molecules in development have the potential to revolutionize the practice of psychiatry. Often, drug development clinical trials in psychiatry are directed more toward developing molecules that provide a better tolerability profile or provide some incremental improvement in drug delivery. As such, the inclusion/exclusion criteria are relatively narrow. Subjects with significant medical problems, drug interactions, multiple comorbid psychiatric conditions, suicidal ideation, substance use disorders, and significant social-economic burdens such as homelessness are often excluded from participation. In addition, pediatric and geriatric populations are often not included in clinical trials. Pediatric studies are often included in the additional studies required by the FDA in the post-marketing phase of drug development. Excluding these patients from the trials serves the purpose of creating a set of results that favor the developing drug product but produce results that do not necessarily serve the greater good as the complicated patients that comprise a significant portion of patients in clinical practice are not reflected in the results. [44, 46] Along these same lines, the US Department of Justice estimates that up to 43% of inmates may have a history of mental illness and up to 40% of inmates are receiving treatment for mental health concerns [74]. In addition, growth in the forensic psychiatric population within the behavioral healthcare system continues to grow. Clinical trials with these populations are fraught with ethical complications, and it is important to remember the IRB regulations regarding the use of prisoners in clinical trials. Notwithstanding the complications of getting informed consent from judges, and the challenges of working with a population with highly complex illnesses, the potential for coercion in this population is high. Clearly, the same standards of treatment for incarcerated subjects should exist as for any other trial participant. Similarly, there should be no special incentives provided such as gaining access to certain privileges or leverage in decisions around parole. Subjects who are incarcerated may be motivated/coerced by perceived incentives – simply spending time outside of the cell or prison milieu may be viewed as an incentive. Clearly monetary incentives are viewed differently in prison relative to the community. A prisoner representative of the IRB must attend the meeting where the study is reviewed [12]. Financial payments for participation are often reviewed with higher levels of scrutiny by IRBs. A perception exists that patients with psychiatric diagnoses, especially those that are unemployed or on disability, may be coerced into participation by smaller amounts of remuneration than the general population. Very little empiric evidence is available to support this notion. However, concern does exist about

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providing cash payments to subjects that might be at risk for substance use. But again, there is no evidence to support that providing non-cash payments reduces this risk. IRBs have wide ranging policies and guidance for providing remuneration to vulnerable subjects.

5.7 Conclusions As evidenced in this chapter, drug development is an expensive, high risk, and long process. Once molecules with potential therapeutic effect are developed, they must have extensive in  vitro and animal testing before entering trials in humans. A sequence of studies is conducted in humans to determine the characteristics of the drug in the body and its efficacy and safety. It is a highly regulated process, and ethical considerations are given paramount importance.

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Chapter 6

Post-Approval Research in Drug Development: Priorities and Practices David Williamson, Jack Sheehan, and Ella Daly

Abstract  A prescriber might ask if a new medication is a good option for use in the patients he or she sees in clinic, with their particular blends of demographic and comorbid clinical characteristics. Is this medicine more effective, safe, tolerable, or affordable than the options used in the past? A payer may ask if the new medication offers a more effective, cost-efficient, or convenient alternative to those treatments already being covered. These are the types of questions that are often difficult to answer on the basis of the clinical trials used to support a medication’s initial approval, which are generally designed to evaluate a medication’s efficacy, safety, and tolerability in narrowly defined patient populations. Consequently, in order to answer  the questions most relevant to key stakeholders (i.e., regulators, patients, and clinicians), it is important to continue to examine a medication’s impact and characteristics after it has received regulatory approval. Such studies vary in their purpose, scope, and methodology. In this chapter, we review the types of questions most likely to be investigated after regulatory approval, the methods generally used to investigate them, and the characteristics typically considered when prioritizing the allocation of resources. Keywords  Phase 4 trials · Post-approval research The process by which a new drug becomes a candidate for approval by the US Food and Drug Administration (FDA) and similar regulatory authorities has been extensively characterized throughout this volume. In seeking approvalw from regulatory D. Williamson University of South Alabama College of Medicine, Departments of Psychiatry and Neurology, Mobile, AL, USA J. Sheehan Independent Medical Consultant, Doylestown, PA, USA e-mail: [email protected] E. Daly Janssen Scientific Affairs, LLC, Titusville, NJ, USA © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 M. Macaluso et al. (eds.), Drug Development in Psychiatry, Advances in Neurobiology 30, https://doi.org/10.1007/978-3-031-21054-9_6

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authorities, drug developers must weigh a host of considerations, including precise definitions of the diseases being treated, populations being studied, trial designs and statistical methods most appropriate to characterize efficacy, and the medication’s safety and tolerability. This is a costly, resource-intensive process; for central nervous system medications, recent estimates suggest the total development expenditure is approximately $766 million [23]. Manufacturers seek to discover and develop a medication that addresses a key unmet medical need and is efficacious, safe, tolerable, and convenient for patients. However, for many products, the process of gaining regulatory approval is only part of the story. Much of what is known about the medications we use is based on research performed after approval by regulatory authorities. This research can include comparisons to other drugs or modalities of treatment, investigations of “real-world” samples that focus on effectiveness rather than efficacy, and examinations of drug performance in different populations or indications. These studies may be conducted independently from the pharmaceutical industry, but pharmaceutical companies are often active in these post-approval efforts. In this chapter, we will provide one perspective on the types of priorities, decisions, and practices that drive these investigations, with a particular focus on considerations that would be relevant for drug development in neurology or psychiatry.

6.1 Priorities When seeking regulatory approval for a medication, the top priority is to provide sufficient evidence of benefit for the condition being treated in the target patient population. After approval, a variety of questions concerning the medication may be asked, but all are generally driven by a central consideration: what do patients, prescribers, and/or payers (e.g., insurance companies) need to know about the medication, and how does it fit into the existing or anticipated marketplace? The responses to this question may vary dramatically depending on the condition or patients being treated, the number and characteristics of existing competing products or treatment modalities, availability of treatment guidelines for the disease, and the resources of the company funding or collaborating in the research.

6.2 Regulatory Commitments During the post-approval process, regulatory agencies may require additional evidence to better understand questions that were outstanding at the time of approval. Such studies may focus on aspects such as long-term safety, efficacy, or optimal dosing in specific populations. For example, additional studies may be planned to evaluate the efficacy and safety of a medication in a pediatric population after the initial approval was granted for adults only. Similarly, some medications are

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initially approved as adjunctive therapies, and following approval, regulatory authorities may pose questions about a medication’s potential utility as a monotherapy agent. For all products, once regulatory approval has been received, the manufacturer must submit periodic safety update reports (or, in the United States, periodic adverse drug experience reports, better known as PADER), where case reports with serious unlisted events are presented in a narrative or tabular format. For a limited number of products, there may be a risk evaluation and mitigation strategy (REMS) required at the time of approval. A REMS is a drug safety program that the FDA may require for products with serious safety concerns to help ensure the benefits of a medication outweigh its risks [21]. These types of programs or registries are typically conducted by the pharmaceutical company manufacturing the drug, often with the assistance of a specialized vendor, with specific metrics regularly shared with the FDA on a predetermined schedule. The FDA may in turn seek additional data or clarifications in the form of information requests, to which the manufacturer must respond to within a given timeframe.

6.3 Further Clinical Considerations A variety of clinical questions may stimulate investigations after a medication’s initial regulatory approval for a specific indication. The fundamental questions of general efficacy, safety, and tolerability of a product are addressed by pivotal trials, phase 3 clinical trials that generate the core evidence that informs the initial approval decision by regulatory authorities. However, these data never answer every clinical question, and the patients included in phase 3 studies may not be broadly representative of real-world patient populations. Additionally, placebo effects observed in trials of drugs targeted at neurological or psychiatric conditions can be substantial [9, 11, 12]. Consequently, in order to maximize the likelihood of finding valid evidence that a treatment is working in the population for whom it is intended, inclusion and exclusion criteria for phase 3 clinical trials are designed to create a relatively homogenous clinical population. However, this strategy may exclude potentially relevant strata of disease severity, comorbidities, or other aspects of clinical presentation that inform everyday clinical decision-making on a regular basis. Furthermore, behavioral or operational aspects of everyday clinical situations (e.g., nonadherence, missing scheduled appointments, unexpected delays in treatment coverage or supply) are generally minimized or eliminated by the structure of formal clinical trials. In addition, for ethical reasons, pivotal trials may exclude patients perceived to have elevated safety concerns so as not to confound the safety signal, and there may be reluctance to use an investigational agent in these populations during drug development. Finally, many trials are international in nature, both for reasons of cost and varying regulatory requirements [16]. The cumulative impact of these clinical trial features is that some populations may be relatively understudied, despite there being sufficient evidence that a

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medication is effective, safe, tolerable, and convenient enough in the intended clinical population to receive regulatory approval. Such patient characteristics may include gender, age (e.g., those aged ≥65 years or  0.9)] [11].

14.4 Conclusion and Clinical Translation The studies reviewed here pertain only to the potential relevance of MAO-B in psychosis and schizophrenia. Major limitations include that most studies are not necessarily matched for sex, age, smoking, or body mass index. MAO-B is sensitive to the effects of age, sex, and cigarette smoking [114], as demonstrated in postmortem [25], genetic [91, 92], and peripheral studies [64]. Further limitations among clinical studies are the use of different combinations of antipsychotic treatments and smoking status among patient groups that may affect the results. Also, chronic treatment with antipsychotics may compromise psychosis severity quantification, especially in postmortem samples. Other limitations inherent to postmortem studies may contribute to the variable results. With respect to peripheral findings, while MAO-B activity may be related to alterations in platelets rather than central MAO-B, there are other considerations [42]. When results are reported in equivalent units, values of MAO-B activity for similar diagnostic groups may vary considerably from one study to another,

↑ [11C] L-deprenyl- D2 radioactivity

[11C] L-deprenyl-D2

11

Logan Five (4 F, et al. 2000 1 M) (age range, 23–73 years)

Fowler Five (age et al. 1995 range, 43–64 years)

2

C-labeled suicide ↑ (ROIs) enzyme inactivators, clorgyline, L-deprenyl (1st generation) [11C] L-deprenyl ↑ [11C] L-deprenyl- D2 11 & [ C] radioactivity L-deprenyl-D2 (2nd generation)

MAO-B activity ↑ (all ROIs except brain stem)

Fowler Five (age et al. 1987 range, 26–86 years)

Reference Subjects (HC) Radiotracer 1 [14C] DMPEA Shinotoh Four M (age et al. 1987 range, 48–70 years)

Occipital cortex, cingulate cortex, thalamus, basal ganglia, cerebellum, whole brain (global) Frontal cortex, occipital cortex, temporal cortex, parietal cortex, basal ganglia, thalamus, cerebellum, global

Regions of interest (ROIs) Frontal cortex, temporal cortex, occipital cortex, basal ganglia (caudate, putamen, and pallidum), thalamus, cerebellum, brain stem corpus striatum, thalamus, cortex, and brainstem

Table 14.4  Clinical PET studies quantifying MAO-B density in different human brain regions

Irreversible trapping, nonpolar metabolites, sensitive to blood flow

Brain-penetrant metabolites

Brain-penetrant metabolites: R(—) methamphetamine and R(—) amphetamine)

↑ selectivity, ↑ specificity (phenelzine reduced brain uptake (one subject); prior L-deprenyl treatment blocked brain retention) Reduced rate of trapping, ↑ MAO-B sensitivity & selectivity

Reduced rate of trapping, ↑ MAO-B sensitivity, ↑ selectivity, good reproducibility (test-retest performed (7–27 days apart) showed acceptable results¥)

(continued)

Cons Irreversible trapping (nonspecific binding), too quickly metabolized

Pros ↑ selectivity, brain uptake, ↑ specificity (L-deprenyl (10 mg/kg) reduced radioactivity)

14  Monoamine Oxidase B (MAO-B): A Target for Rational Drug Development… 353

↑ [11C] L-deprenyl- D2 radioactivity

Arakawa Six (4 M, 2 F) [11C] et al. 2017 (age range, L-deprenyl-D2 21–62 years)

Regions of interest (ROIs) Cerebellar cortex, caudate, putamen, frontal cortex, temporal cortex, anterior cingulate cortex, thalamus, and pons Cerebellum, hippocampus, lateral frontal cortex, lateral occipital cortex, lateral parietal cortex, lateral temporal cortex, medial frontal cortex, putamen, thalamus Pros good identifiability, polar metabolites, ↑ MAO-B selectivity, ↑ sensitivity, good reproducibility (test-retest performed (5 ± 1 weeks apart showed acceptable variation£) Reduced rate of trapping, ↑ MAO-B sensitivity, ↑ selectivity, good reproducibility (test-retest performed (same day morning and afternoon) showed acceptable results€) Brain-penetrant metabolites

Cons No specificity quantification

↑ MAO-B activity in the brain regions of interest; 1, Parallel experiment conducted for MAO-B inhibition: C3H adult mice (M): pretreatment with doses (0, 0.01, 0.1, 10 mg/kg, i.v.) of L-deprenyl & clorgyline - 10 mg/kg); 2, MAO-B inhibition performed using Phenelzine (one subject) [L-deprenyl (15 mg)]; λk3*, model term proportional to MAO-B (validated outcome measure for [11C] L-deprenyl-D2); K1, the plasma to brain transfer constant that is related to blood flow; k3, rate constant (MAO-B binding quantified by two tissue compartment model (2TCM) with three rate constants (K1, k2, and k3) using metabolite-­corrected plasma radioactivity) and λk3** = (K1/k2) × k3; ¥1) global value (mean difference − 2.1 ± 4.7%) 2) mean % change in eight brain regions (−2.84 ± 7.07%) 3) test-retest variability of λk3* values (mean difference − 2.84 ± 7.07%), high correlation (r2 = 0.98; p a nterior cingulate cortex>frontal cortex>temporal cortex>Pons>cerebellar cortex

Reference Subjects (HC) Radiotracer [11C]SL25.1188 Rusjan, Seven (4 M, et al. 2014 3 F; age range, 19–49 years)

Table 14.4 (continued)

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presumably because of variations in platelet preparation, assay procedures, and the apparently large normal range of human platelet MAO-B activity. Large variations from study to study are also due to differences in laboratory equipment, assay procedures, and statistical analyses. Furthermore, among genetic studies, power concerns are important caveats. In preclinical studies, MAO-B knock-out mice may not display altered extracellular levels of dopamine owing to the significant adaptive upregulation of the D2-like dopamine receptors and hypersensitivity of D1 receptors [44]. The degradation of dopamine is mediated by both MAOs, but the relative contribution of each isoenzyme differs in relation to the species and the tissue under consideration [49, 115]. Finally, MAO-B is predominantly found in astrocytes (and serotonin releasing neurons), and its overexpression in activated astrocytes has led to the proposition that MAO-B could be a reliable biomarker for astrocytosis in disease states [116– 118]. Greater MAO-B levels occur in neurodegenerative diseases with astrogliosis. MAO-B was also significantly associated with other astroglial markers such as glial fibrillary acidic protein (GFAP) [119]. For example, a postmortem study showed increased levels of MAO-B in the plaque-associated astrocytes in Alzheimer’s disease in temporal, parietal and frontal cortices [120]. The findings summarized in this chapter indicate that although the role of MAO-­ B in schizophrenia is still inconclusive, preclinical, peripheral, postmortem, and genetic studies suggest it is possible that there is altered MAO-B activity in schizophrenia. The most supported finding is the reduced MAO-B activity in the peripheral tissues of patients, particularly in chronic paranoid schizophrenia; however, previous studies are confounded by cigarette smoking. Additionally, some MAO-B knock-out mice studies resulted in hyperdopaminergic states and behavioral disinhibition, which is broadly in line with the hyperdopaminergic hypothesis of schizophrenia. Moreover, preclinical studies utilizing MAO-B inhibitors (selegiline/L-deprenyl) suggest that dopamine metabolism is altered with higher concentrations (10  mg/kg) [39] and chronic administration (21  days) [121]. Additionally, several human studies have evaluated the selective MAO-B inhibitor, selegiline, in the treatment of negative symptoms [20, 21]. Bodkin et al. [22] found that selegiline was significantly more effective than placebo for the treatment of predominant negative symptoms [122]. Further, a selective MAO-B inhibitor, rasagiline which is up to 15 times more potent than selegiline, may be of clinical benefit for negative symptoms [23]. Together, this indicates the potential involvement of MAO-B in the pathophysiology of schizophrenia and warrants the need for in vivo human studies, potentially usable as a biomarker or stratification tool via the use of highly selective PET radioligands, which target MAO-B. Acknowledgments  This review chapter was done as part of the research undertaken, thanks in part to funding from the Canada First Research Excellence Fund, awarded to the Healthy Brains for Healthy Lives initiative at McGill University. I would like to acknowledge and thank my research colleagues for their continued support and guidance throughout the preparation of this review chapter.

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Declaration of Interest  The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this chapter. Credit Authorship Contribution Statement  Kankana Nisha Aji: conceptualization, methodology, and writing – original draft. Jeff Meyer: validation and writing – review and editing. Pablo M. Rusjan: validation and writing – review and editing for the PET section. Romina Mizrahi: supervision, validation, and writing – review and editing. Source of Funding  The preparation of this review chapter received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

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77. Owen F, Bourne RC, Crow TJ, Fadhli AA, Johnstone EC. Platelet monoamine oxidase activity in acute schizophrenia: relationship to symptomatology and neuroleptic medication. Br J Psychiatry. 1981;139:16–22. 78. DeLisi LE, Wise CD, Bridge TP, Rosenblatt JE, Wagner RL, Morihisa J, et al. A probable neuroleptic effect on platelet monoamine oxidase in chronic schizophrenic patients. Psychiatry Res. 1981;4(1):95–107. 79. Orologas AG, Buckman TD, Eiduson S. A comparison of platelet monoamine oxidase activity and phosphatidylserine content between chronic paranoid schizophrenics and normal controls. Neurosci Lett. 1986;68:293–8. 80. Fowler JS, Volkow ND, Wang GJ, Pappas N, Logan J, MacGregor R, et  al. Inhibition of monoamine oxidase B in the brains of smokers. Nature. 1996;93(24):14065–9. 81. Berlin I, Said S, Spreux-Varoquaux O, Olivares R, Launay JM, Puech AJ. Monoamine oxidase A and B activities in heavy smokers. Biol Psychiatry. 1995;38(11):56–761. 82. Fowler JS, Wang GJ, Volkow ND, Franceschi D, Logan J, Pappas N, et al. Maintenance of brain monoamine oxidase B inhibition in smokers after overnight cigarette abstinence. Am J Psychiatry. 2000;157(11):1864–6. 83. De Leon J, Dadvand M, Canuso C, White AO, Stanilla JKSG. Schizophrenia and smoking: an epidemiologic survey in a state hospital. Am J Psychiatry. 1995;152:453–5. 84. Wyatt RJ, Murphy DL, Belmaker R, Cohen S, Donnelly CH, Pollin W. Reduced monoamine oxidase activity in platelets: a possible genetic marker for vulnerability to schizophrenia. Science.1973;179:916–8. 85. Reveley MA, Reveley AM, Clifford CA, Murray RM. Genetics of platelet MAO activity in discordant schizophrenic and normal twins. Br J Psychiatry. 1983;142:560–5. 86. Baron M, Levitt MPR. Low platelet monoamine oxidase activity: a possible biochemical correlate of borderline schizophrenia. Psychiatry Res. 1980;3(3):329–35. 87. Dann J, DeLisi LE, Devoto M, Laval S, Nancarrow DJ, Shields G, et  al. A linkage study of schizophrenia to markers within Xp11 near the MAOB gene. Psychiatry Res. 1997;70(3):131–43. 88. Wei J, Hemmings GP. A study of linkage disequilibrium between polymorphic loci for monamine oxidases A and B in schizophrenia. Psychiatr Genet. 1999;9(4):177–81. 89. Grant P, Gabriel F, Kuepper Y, Wielpuetz C, Hennig J. Psychosis-proneness correlates with expression levels of dopaminergic genes. Eur Psychiatry. 2014;29:304–6. 90. Carrera N, Sanjuán J, Moltó MD, Carracedo Á, Costas J. Recent adaptive selection at MAOB and ancestral susceptibility to schizophrenia. Am J Med Genet Part B Neuropsychiatr Genet. 2009;150B(3):369–74 91. Coron B, Campion D, Thibaut F, Dollfus S, Preterre P, Langlois S, et al. Association study between schizophrenia and monoamine oxidase A and B DNA polymorphisms. Psychiatry Res. 1996;62(3):221–6. 92. Wei J, Hammings GP.  Allelic association between dinucleotide repeats at the monoamine oxidase loci and schizophrenia. Eur Psychiatry. 1998;13(8):407–10. 93. Gassó P, Bernardo M, Mas S, Crescenti A, Garcia C, Parellada ELA.  Association of A/G polymorphism in intron 13 of the monoamine oxidase B gene with schizophrenia in a Spanish population. Neuropsychobiology. 2008;58(2):65–70. 94. Wei YL, Li CX, Li SB, Liu YHL. Association study of monoamine oxidase A/B genes and schizophrenia in Han Chinese. Behav Brain Funct. 2011;7(1):42. 95. Andreou D, Söderman E, Axelsson T, Sedvall GC, Terenius L, Agartz I, et al. Polymorphisms in genes implicated in dopamine, serotonin and noradrenalin metabolism suggest association with cerebrospinal fluid monoamine metabolite concentrations in psychosis. Behav Brain Funct. 2014;10:26. 96. Sun J, Jayathilake K, Zhao Z, Meltzer HY.  Investigating association of four gene regions (GABRB3, MAOB, PAH, and SLC6A4) with five symptoms in schizophrenia. Psychiatry Res. 2012;198:202–6.

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115. Tipton KF, O’Carroll AMMJ.  The catalytic behavior of monoamine oxidase. J Neural Transm. 1987;23:25–35. 116. Levitt P, Pintar JE, Breakefield XO.  Immunocytochemical demonstration of monoamine oxidase B in brain astrocytes and serotonergic neurons. Proc Natl Acad Sci U S A. 1982;79(20): 6385–9. 117. Nakamura S, Kawamata T, Akiguchi I, Kameyama M, Nakamura N, Kimura H. Expression of monoamine oxidase B activity in astrocytes of senile plaques. Acta Neuropathol. 1990; 80(4):419–25. 118. Ekblom J, Jossan SS, Oreland L, Walum E, Aquilonius SM. Reactive gliosis and monoamine oxidase B. J Neural Transm. 1994;41:253–8. 119. Tong J, Rathitharan G, Meyer JH, Furukawa Y, Ang LC, Boileau I, et al. Brain monoamine oxidase B and A in human parkinsonian dopamine deficiency disorders. Brain. 2017; 33(6):863–71. 120. Saura J, Luque JM, Cesura AM, Da PM, Chan-Palay V, Huber G, et al. Increased monoamine oxidase b activity in plaque-associated astrocytes of Alzheimer brains revealed by quantitative enzyme radioautography. Neuroscience. 1994;62(1):15–30. 121. Lamensdorf I, Youdim MBFJ.  Effect of long-term treatment with selective monoamine oxidase A and B inhibitors on dopamine release from rat striatum in  vivo. J Neurochem. 1996;67(4):1532–9. 122. Jungerman T, Rabinowitz D, Klein E.  Deprenyl augmentation for treating negative symptoms of schizophrenia: a double-blind, controlled study. J Clin Psychopharmacol. 1999;19(6):522–5.

Chapter 15

Genomics in Treatment Development Yogesh Dwivedi and Richard C. Shelton

Abstract  The Human Genome Project mapped the 3 billion base pairs in the human genome, which ushered in a new generation of genomically focused treatment development. While this has been very successful in other areas, neuroscience has been largely devoid of such developments. This is in large part because there are very few neurological or mental health conditions that are related to single-gene variants. While developments in pharmacogenomics have been somewhat successful, the use of genetic information in practice has to do with drug metabolism and adverse reactions. Studies of drug metabolism related to genetic variations are an important part of drug development. However, outside of cancer biology, the actual translation of genomic information into novel therapies has been limited. Epigenetics, which relates in part to the effects of the environment on DNA, is a promising newer area of relevance to CNS disorders. The environment can induce chemical modifications of DNA (e.g., cytosine methylation), which can be induced by the environment and may represent either shorter- or longer-term changes. Given the importance of environmental influences on CNS disorders, epigenetics may identify important treatment targets in the future. Keywords  Cytochrome enzymes · Drug–drug interactions · Drug metabolism · Enrichment strategies · Epigenetics · Genetics · Genomics · Genome-wide association studies · Pharmacogenomics · Uridine 5′-diphospho-glucuronosyltransferases

Y. Dwivedi · R. C. Shelton (*) Department of Psychiatry and Behavioral Neurobiology, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 M. Macaluso et al. (eds.), Drug Development in Psychiatry, Advances in Neurobiology 30, https://doi.org/10.1007/978-3-031-21054-9_15

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The Human Genome Project was an international effort to determine the base pair sequence of the human genome and mapping of individual genes. The project began with great promise in 1990, and the initial publication of most of the sequence and a tentative set of genes occurred in 2003 [1]. The complete mapping of the 3 billion base pairs in the human genome was an enormous task that required the efforts of many labs distributed across the globe. The promises of the Project were ambitious and included the ability to understand diseases at the most fundamental level. The Project was expected to discover mutations linked to diseases, allowing scientists to develop new medicines and other treatments, to predict response to treatment, and to both predict and prevent disease [2–5]. The results of the Project were no less than revolutionary, and it is hard to image a science without the sequence of human DNA. There certainly have been many advances in the understanding of human diseases and the development of treatments as a result. This has been particularly true in cancer genomics, in which mutations have been linked to specific cancers, which has led to an improved understanding of the underlying physiology of disease, leading to new treatments [6]. Other areas significantly impacted by genomics have included anticoagulant therapy [7, 8], infectious disease surveillance and treatment [9], Alzheimer’s disease [10], and many others. A very large number of drugs now include pharmacogenomic recommendations in FDA-approved drug labeling [118]. However, much of the use of genomic information in practice now has to do with drug metabolism and adverse reactions. Outside of cancer biology, the actual translation of genomic information into novel therapies has been limited. The Human Genome Project produced some significant surprises. A key unexpected finding is the number genes. Prior to the Project, estimates of the number of genes in the human genome ranged from 100,000 to as high as 150,000, which roughly corresponds to the number of proteins in the body [12]. However, during various stages of the Project, this number declined progressively to the current estimate of about 22,300 [13]. The large number of proteins can be explained by the fact that single genes can code for several proteins through alternative splicing in which exon-coded RNAs can be cleaved into multiple variations representing different types of proteins. Also surprising is that only about 1.5% of the human genome is in the form of genes [14], leaving massive amounts of genetic material uncharacterized  – as much as 2.95 billion bases. This intergenic (initially called “junk”) DNA was a mystery that has gradually emerged as being important in human diseases. In addition, environmental influences on DNA referred to as epigenetics have also become very important in our understanding of human disease and potential treatment targets. These will be discussed more below.

15.1 Pharmacogenomics and Drug Development Drug metabolism is the process by which the body chemically modifies medications to facilitate elimination. This process is divided into two phases: Phase I reactions inactivate drugs through direct chemical modifications; this process

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can also change drugs into active metabolites or convert prodrugs to their active forms. These reactions typically involve oxidation, reduction, or hydrolysis of the parent drug. Phase II reactions convert drugs or metabolites into polar forms that can be eliminated [15]. This can involve the addition of many different molecules to the basic structure of the drug. Examples of these processes include methylation, sulfation, acetylation, glucuronidation, glutathione conjugation, and glycine conjugation. There can also be phase III reactions involving further chemical modifications. For most drugs, this involves conversion into water soluble (i.e., hydrophilic) forms that can be eliminated. The most prominent of the phase I enzymes are members of the cytochrome P450 (CYP) superfamily of proteins. These are monooxygenases that serve a wide range of biological processes in addition to their roles in drug metabolism [16]. Most psychotropics (in fact most medications) are metabolized via these enzymes. These comprise a large number of members; the human genome codes for 116 genes and pseudogenes across 18 families of cytochrome P450 genes and 43 subtypes [17]. Each family involves several related subtypes; for example, the CYP2 family includes 16 subtypes. For psychotropics, the most significant of those include CYP2B6, CYP2C9, CYP2C19, and CYP2D6. Other important psychotropic metabolizing enzymes include CYP1A2 and CYP3A4. Medications can also be metabolized by other enzymes (e.g., monoamine oxidase) or directly conjugated by several enzymes including uridine 5′-diphospho-glucuronosyltransferases (UGT) that are responsible for glucuronidation, the addition of glucuronic acid to a drug. Together, these and other enzymatic processes are responsible for drug elimination. The human genome contains a very large number of mutations, gene duplications, or deletions involving drug metabolizing enzymes. This leads to wide variation in the metabolism of drugs. Metabolic activity is divided into several categories, including poor (i.e., little to no metabolic activity), intermediate (i.e., low), extensive (normal), rapid (high), or ultrarapid (very high) metabolism. Not surprisingly, understanding the metabolic pathways for drug elimination is an important part of drug development. Cytochrome P450 enzymes were first discovered in rat liver in 1955 [18] and therefore were known long before gene sequencing existed. The existence of subfamilies of cytochrome enzymes and that there were large variations in their activity has likewise been known for decades. The assessment of drug metabolism has traditionally relied on several components. The most basic step is preclinical, which will be discussed in greater detail below. The first step in humans, which is completed in phase I of drug development, involves a full characterization of drug pharmacokinetics. This earliest studies in humans usually involve single ascending dose studies in which groups of volunteers are given various doses and medication levels are measured in the blood. In this step, variations in blood levels are determined, and side effects are identified. Typically, the occurrence of side effects identifies a maximum tolerated dose (MTD) in humans. These are typically followed by multiple ascending dose studies, which more fully describe the kinetics of the expected dose range. In addition, other aspects of pharmacokinetics can be determined, including the effects of age, sex, race, and the presence or absence of food.

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A classic approach to determine both important enzymes that metabolize medications and potential drug–drug interactions are drug coadministration studies. These involve studies in which drugs that are known to be metabolized by a particular enzyme are administered along with the medication under development. A classic example of this is the concomitant administration of a new medication with debrisoquine, a medication known to be metabolized by CYP2D6 [19]. These drugs can be coadministered, and the impact of the new drug on debrisoquine blood levels can determine if there are significant drug–drug interactions; CYP2D6 inhibitors will increase debrisoquine levels. In addition, drugs that are known to induce (i.e., increase the activity of) specific enzymes can be coadministered along with the new medication. For example, ketoconazole is a potent inhibitor and rifampicin is an inducer of CYP3A4, and coadministration with a drug in development can indicate whether this enzyme is involved in the metabolism of the new medication [20]. There are a number of examples of medications that can be coadministered to determine CYP activity. This process can also identify which metabolic enzymes have the greatest impact on a drug, designated the primary pathway, and which are less important but still involved in metabolism, referred to as secondary pathways. This process is important not only in predicting potential drug–drug interactions but also in determining whether specific genetic variants of drug metabolizing genes will affect drug blood levels. Some enzymes are subject to induction, which is an increase in metabolic activity caused by a drug or other substance. A classic example is the induction of CYP3A4. The increase in enzymatic action of CYP3A4 is the product of the binding of the drug or other compound to the pregnane X receptor, which forms a heterodimer with the retinoid X receptor. This complex then binds to the XREM portion of the gene for CYP3A4, which increases gene transcription. This results in a larger than normal amount of CYP3A4 production, increasing activity of the enzyme. Well-known inducers include carbamazepine, oxcarbazepine, topiramate, rifampicin, efazirenz, nevirapine, and modafinil, although the potency of induction can vary considerably. In recent years, preclinical models have been used to characterize drug absorption, distribution, metabolism, and excretion. With regard to drug metabolism, these have included in vitro, in vivo, or in silico methods [15]. In vivo methods involve the administration of drugs to animals such as rodents or zebra fish. In vitro approaches can be done at large scale to test for drug metabolism, interactions, toxicity, or other properties [15]. With regard to drug metabolism, model systems have been developed to characterize enzyme activity. These include hepatic cell cultures and the extraction of microsomes, which are subcellular fractions of endoplasmic reticulum that contain CYP and UGT enzymes. These screening methods allow for a full characterization of metabolism prior to administration to humans. This, in turn, simplifies early stage drug testing, which can focus on known metabolic pathways. A final approach involves in silico (meaning, in a computer) methods. These involve computational tools that can match drug structure to enzyme, which have been determined by X-ray crystallography and nuclear magnetic resonance

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methods [15]. Drug models can then be fitted into enzyme structures to determine likely metabolic pathways. This can be used with other proteins like receptors or transporters. While these and related computational models may not identify all such interactions, they can also reduce the time to develop new molecules. (For a more complete discussion of in vitro and in silico models, see Issa TA et al. [15]). Once drug metabolic pathways are identified, then variations in drug level can be predicted. Variations in drug metabolism can involve either loss or gain of single nucleotide polymorphisms (SNPs), meaning a single base substitution in the gene or other related genetic changes that can alter the metabolic activity of a protein such as a SNP enzyme. Genes for specific enzymes can also be deleted or duplicated. In the case of deletion, part or all of a gene can be removed from the genome, rendering the body incapable of making the protein. Gene duplication occurs when a person’s DNA contains multiple copies of the same gene. All genetic variations can occur in either heterozygous or homozygous forms; in the former, a person can have one of the two copies of a gene that is affected. In the latter, it is two copies. In the case of loss of function mutations, the heterozygous state usually involves a reduction, but not total loss of enzymatic activity. When homozygous, this can involve a severe reduction or even complete loss of activity of that enzyme. For example, in the case of a homozygous deletion of the CYP2D6 enzyme, there is no metabolic activity, meaning that people with the double deletion can run extremely high blood levels of drug. The gain of function alleles or gene duplications has the opposite effect. The heterozygous state will produce a reduction in expected blood levels while the homozygous state can cause dramatic reductions in levels. Therefore, determining metabolic pathways is a critical element in the drug development process. The effects of gain or loss of function of a metabolizing enzyme is made more complicated by two factors. The first are heterologous gene combinations, which involve varying combinations of normal, gain, or loss of function alleles. The combination of an extensive metabolizing allele with either a loss or gain is the typical heterozygous state described above. However, other heterozygous combinations can create more complexity. An example would be the combination of gain and loss of function alleles. The most extreme would be a combination of a gene deletion with a gene duplication. These kinds of combinations result in a variety of metabolism that do not fit into the individual poor to ultrarapid metabolizer states noted earlier. This is why blood levels tend to be continuously distributed and not into five neat metabolism groups. The second factor is that while medications usually have a primary metabolic pathway involving a single enzyme, there are also secondary pathways that can compensate for a reduction in metabolic activity. For example, while the primary metabolic pathway for the tricyclic antidepressant amitriptyline is CYP2D6, it is also metabolized by CYP1A2, CYP2C9, CYP2C19, CYP3A4, and UGT1A4. Therefore, a complete loss of function of CYP2D6 does not necessarily result in inevitable toxicity (although the levels would be higher). By contrast, gain of function alleles or gene duplication of the primary metabolizing pathway invariably result in significantly lower blood levels, although this can vary considerably depending on whether it is heterozygous or homozygous and whether it is a SNP or

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gene duplication. Even in situations in which the primary pathway predicts extensive (normal) metabolism, a rapid or ultrarapid metabolizer status of a secondary pathway may result in lower than expected blood levels. For this reason, in the case of an unexpected negative outcome such as poor response or toxicity, a blood level is warranted (if available) even if the predicted metabolizer status is extensive (i.e., normal). Taken together, all these factors indicate that a thorough understanding of the enzymatic pathways involved in drug metabolism is a critical aspect of drug development.

15.2 Genomics and Drug Development The decoding of the human genome came with tremendous hope that it would lead to novel treatments for a full range of medical disorders. The expectation was that the whole drug discovery process would change. Genomic information could lead to the discovery of disease pathways, molecular diagnostics, novel drug target prediction, drug response markers, methods for optimizing drug choice (i.e., personalized medicine), improved safety and efficacy, and other effects [3]. In some ways, that promise has been realized. A variety of mutations of specific genes has been shown to be associated with increased breast cancer risk, including mutations of BRCA1 and BRCA2, p53, PTEN, STK11, CHEK2, ATM, BRIP1, and PALB2 [21], and genetic testing has become a routine medical practice. BRCA1/2 mutations are also associated with risk for other malignancies, including ovarian cancer. Olaparib, an inhibitor of poly (ADP-ribose) polymerase (PARP), originally approved for advanced ovarian cancer in patients with certain BRCA1/2 mutations [22]. This is an example of genomic personalized (or precision) medicine – i.e., of matching a treatment to cancers associated with specific genetic mutations. Enrichment Strategies  Conducting clinical trials that use a specific genomic or other biomarker that is associated with better response to a particular medication is an example of an enrichment strategy. According to the US FDA, “enrichment is the prospective use of any patient characteristic to select a study population in which detection of a drug effect (if one is in fact present) is more likely than it would be in an unselected population.” [23] Trials of this type can determine if specific genetic mutations, or any other characteristic, are associated with preferential response to certain medications. The biomarker can then be used to select participants for subsequent trials [18]. If trials are positive, the US FDA and other regulatory agencies then require the product labeling, that is, the language used to describe the agency approved indication, to indicate that the enrichment marker, genomic, other biomarker, or other patient characteristic should be present for the medication to be used. Such enrichment strategies not only provide information for clinical practice but also (ideally) increase the likelihood of trial success (i.e., increase study power). (For more information on enrichment, see the relevant FDA guidance document [24]).

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There are at least three possible enrichment approaches: (1) strategies to decrease variability, (2) prognostic enrichment strategies, and (3) predictive enrichment [18]. Strategies to decrease variability narrow the participant pool using a biomarker or other characteristic, thereby excluding participants who are unlikely to contribute to a positive study endpoint [24]. Examples would be excluding people whose condition is likely to improve spontaneously, those who are likely to show enhanced placebo effect, or participants who are likely to have highly variable outcomes. Most clinical trials employ inclusion and exclusion criteria to reduce variability and could be considered forms of enrichment. For example, trials in patients with treatment resistant major depressive disorder typically exclude people with certain comorbid disorders (e.g., obsessive compulsive disorder or post-traumatic stress disorder) and those with greater than five prior adequate antidepressant trials, since they are less likely to respond to either the active treatment or placebo. Patients with borderline personality disorder are usually excluded because of the expectation that they will have highly variable outcomes not related to treatment. The use of exclusion criteria is an attempt to reduce variability by eliminating characteristics that may be associated with reduced drug-placebo differences. Strategies to reduce variability are, in essence, exclusion strategies. That is, they eliminate participants that are unlikely to contribute to drug-placebo differences. This would also apply to other treatments as well, such as device, psychotherapy, or other trials. Other approaches to reduce variability include detailed entry criteria to ensure that enrolled participants have the disease under study, selecting participants who are likely to adhere to the study protocol, enrolling only people with consistent baseline values (e.g., blood pressures or depression severity on repeated testing), or placebo lead-in periods to eliminate placebo responders [24]. It is important to consider inclusion and exclusion criteria when interpreting the results of trials. While the treatment may be effective for people who were excluded from studies, the treatment has not been adequately tested for people with those characteristics and, therefore, may not be effective. If people with certain characteristics are systematically excluded from all trials supporting a treatment, then the treatment cannot be considered evidence based for people with those features [24]. Prognostic enrichment strategies involve the selection of participants based on the likelihood of an event occurring. This is typically some type of negative outcome, for example, recurrence of cancer, relapse of depression or psychosis, or the occurrence of an adverse effect. Depression relapse prevention trials often exclude people who are in their first episode of illness, since a relapse in the study is more likely in recurrent depression. This does not change the relative effectiveness of an active treatment and placebo; it simply makes it more likely to detect meaningful differences [24]. Predictive enrichment strategies are the most relevant to biomarker research, including genomics. These are selection approaches in which certain patient characteristics like genotype or other biomarkers are used to select participants who are likely to respond to a treatment. Rather than determining who is unlikely to respond, as is often the case with strategies to reduce variability, this method identifies those likely to respond to the treatment. More specially, this approach determines who is

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likely to have an increased active versus inactive treatment difference. Such strategies can also be used to identify people who are likely to experience adverse outcomes and who should not receive a treatment. Biomarkers like genotype or other characteristics can help divide people who have a particular condition into those who are more versus less likely to respond to the active treatment [24]. The example of olaparib given above is an example of a prognostic strategy. In that case, BRCA1/2 genotype is used to select the treatment for people with advanced ovarian cancer. Olaparib does not directly target the protein coded by the BRCA genes, breast cancer type 1 or 2 susceptibility proteins, which are tumor suppressor genes. Rather, the medication inhibits the enzyme poly ADP ribose polymerase (PARP), which is a DNA repair protein that tumor cells require to continue replicating. Olaparib is effective in several BRCA1/2 positive cancers, and it is more effective in BRCA1/2 positive than negative cancers, but it has some efficacy even in certain BRCA1/2 negative cancers [25]. Therefore, in the case of olaparib, the identification of the association of the BRCA1/2 mutation to certain cancers did not lead directly to a treatment that targeted the mutated proteins directly. Rather, the treatment targets a protein involved in tumor cell replication that is downstream from the effects of BRCA1/2. People with those mutations appear to be more responsive to olaparib than people without, and therefore, BRCA1/2 mutations can be used as a selection criterion for treatment. However, there is not a direct homology between mutated gene and protein and treatment target. Gene Targeting Therapies  There have been very few examples of genetic mutations leading directly to an underlying pathophysiology that can be targeted by new therapies. Prime examples are therapies directed to receptor tyrosine-protein kinase erbB-2, also known as human epidermal growth factor receptor 2 or HER2 coded by the ERBB2 gene. Overexpression of this oncogene plays a role in the progression of certain breast cancers and probably other types of cancers. Cancers that show overexpression of HER2 (called HER2 positive cancers) can be targeted by trastuzumab, a monoclonal antibody. Other medications that have been approved or are in clinical trials include pertuzumab, margetuximab, and the immunotherapy NeuVax, a peptide vaccine that directs killer T cells to HER2+ cancers. Why then is it difficult to go from a gene mutation to a treatment directly – that is, a treatment that targets the mutated protein? An ideal scenario is one in which a mutation results in a gain of function  – that is, the protein product has a greater effect than the non-mutated wild type [26]. A mutation could also result in an increase in the expression of mRNA and protein. In those instances, a medication could be developed that inhibits the mutated protein, treating the underlying disease. However, most mutations involve loss of function, in which the mutated protein either no longer functions or does so at reduced efficiency. It is possible to conceive of a treatment targeting a loss-of-function mutation. This would be the case, for example, for loss-of-function mutations in tumor suppressor genes [27]. This kind of development program could target the gene or protein directly or the downstream targets of the protein action. Olaparib, discussed earlier, is one example, with the drug targeting a downstream effect of the BRCA1/2 mutation. However,

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this has seldom been the case. The discovery of specific genes and proteins involved in the pathophysiology of a disorder does not necessarily identify a target for a drug, biologic, or other therapy. Although there have many mutations of oncogenes or tumor suppressor genes identified, most have not been developed as direct targets. One promising area is Fragile X syndrome, which is an X-linked dominant disorder that is caused by an expansion of a CGC triplet in the fragile X mental retardation 1 (FMR1) gene on the X chromosome [28]. The protein coded by FMR1 is an RNA binding protein involved in the maturation and pruning of synapses [29, 30]. The FMR1 triplet results in gene silencing, which affects neuroplasticity. The downstream effects are complex (for a review see Maurin et al. [29] and Mila et al. [30]). The downstream effects of FMR1 silencing are possible targets for treatment development. Single-Gene Therapies  Single-gene diseases have been the focus of intense research. Gene replacement therapies have been approved for a range of disorders, including AAV2-hRPE65v2 (also called voretigene neparvovec) that treats a specific type of Leber’s congenital amaurosis type 2, which is related to a mutation in the retinal pigment epithelium-specific 65 kDa protein (RPE65) gene, [31] onasemnogene abeparvovec that treats spinal muscular atrophy related to a mutation in the SMN1 gene, [32] and others [33]. However, relatively few single-gene therapies have been developed. Multifactorial (complex) diseases: Another limitation of genomic approaches, particularly gene therapies, to treatment development is that most illnesses are multifactorial in origin, often called complex diseases. Multifactorial diseases can result from effects of multiple genes and environmental effects. These include not only the most common illnesses like diabetes, hypertension, or cardiovascular disease but also conditions like depression, autism, or schizophrenia. One approach to dealing with these issues is to take a “genotype first” approach, that is, to identify all genomic variants associated with a disease prior to identifying gene by environment effects. The most common genotype first approaches are genome-wide association studies (GWAS). GWA studies evaluate the whole genome to discover associations between gene variants and specific traits, including complex diseases. GWA studies have been applied to many diseases including schizophrenia, bipolar disorder, depression, and other disorders [33–39]. GWAS can identify multiple genes with very small effects on risk, or rare variants with large effects. It would be difficult to develop treatments from polygenic associations unless a coherent pathophysiological model could be constructed, which is often unlikely. Rare genes may be more promising targets, but by their rarity, it might be difficult to identify a large enough population for clinical trials. Converting genomic associations with particular disease states poses a major challenge. One recent development has been to take the results of GWAS analysis to identify predictors of response to individual medications. This approach is neutral with regard to the physiological link between the actual GWAS SNP(s) associated with treatment response and either the underlying disease process or the mechanism of action of a given medication. Rather, it capitalizes on a statistical association

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between one or more SNPs and better or worse response to a medication, making it a predictive enrichment approach as described above. While this has not yielded any approved medications, it is now being used in clinical trials to identify participants who are more likely to respond to a treatment and give a better drug-placebo difference. It is also being used to “resurrect” medications that failed in previous development programs. Traditional genomics, specifically the focus on the sequence of individual genes, may not succeed in developing treatments for most complex diseases. As noted earlier, however, only a tiny fraction of DNA is in the form of genes, and the genome is subject to the epigenetic effects of the environment. The next section will deal with epigenetic targets of treatment development.

15.3 Epigenetic Targets of Drug Development Several lines of evidence show the role of gene x environment interaction in various mental disorders and associated epigenetic interference in the functioning of neuronal circuits [41]. The term, epigenetics, is referred to as long-standing changes in gene expression that are regulated via transcriptional, posttranscriptional, translational, and/or post-translational mechanisms, which does not entail any change in DNA sequence. Epigenetic processes, therefore, are nongenetic and can be impacted by both internal and external stimuli such as hormones, neurotransmitters, drugs, toxins, maternal care, and trauma. In psychiatric illness, most studies have concentrated on epigenetic changes influenced by trauma, stress, and maternal care. Since the changes associated with epigenetic interferences are dynamic, a correlation of the episodic modulations in mental disorders can be correlated with underlying epigenetic changes [42, 43].

15.3.1 Epigenetic Modifications: General Aspects Several types of epigenetic modifications have been proposed. Classic epigenetics involves DNA methylation and histone modification. One of the most common epigenetic modifications is DNA methylation, which involves methylation of the cytosine residue at the 5-position (C5). This occurs by transfer of a methyl group from S-adenosyl methionine to cytosine residues in the dinucleotide sequence of CpG initiated by DNA methyltransferase (DNMT). In general, methylation of cytosine at the 5-position is very stable, which causes reversible changes in gene expression at the transcriptional level [44]. Thus, DNA methylation is inversely correlated with gene expression changes. DNMTs are called “writers” and exist in various isoforms: Dnmt1, 3a, 3b, 2, and 3L. Interestingly, each DNMT has its own regulatory function, which is primarily ascribed to the lack of sequence homology at the N-terminal regulatory domains [45]. Once the cytosine sites are methylated by DNMTs,

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methylated CPGs are targets for DNA-binding domain proteins, also known as “readers.” These include methyl-CPG-binding domain (MBD) proteins and MeCP2, which bind to methylated DNA to induce transcriptional repression [46]. Both of these proteins cause transcriptional repression by recruiting histone deacetylase (HDAC) machinery that further remodel chromatin in such a state that it facilitates a repressed state [47, 48]. DNA methylation can occur in promoter regions and in the gene body; however, more often, CPG methylation in the promoter region represses gene expression [49]. More recently, it has been shown that DNA methylation can also directly silence genes that have non-CPG island (CGI) promoters. In fact, in certain disease conditions, differentially methylated regions occur more frequently within CGI shores or shelves representing relatively low CpG density that flank traditional CPG islands compared with within CPG islands themselves. MeCP2 has the capability to bind to non-CpG methylation sites [49–51] and can assist in gene repression. In addition to its role in gene regulation, DNA methylation also maintains genomic stability by controlling the expression of highly repetitive regions in the genome such as retrotransposons and satellite DNA [53]. Besides traditional CPG methylation, DNAs are hydroxymethylated at the C5 position of a cytosine base, that is, the addition of a CH2OH group at the C5 position. Hydroxymethylation is highly enriched in promoter regions and in intragenic regions; however, it is largely absent from non-gene regions [54]. The mechanism of cytosine hydroxymethylation and its impact on gene expression is not fully known, but a dynamic balance between cytosine methylation and hydroxymethylation exists [55]. Hydroxymethylation is implicated in demethylation and is considered to be a necessary intermediary for methylation by allowing the promoter sites to be prepared for activation [56]. Hydroxymethylation is also assumed to play a role in compensating for the repressing effect of hypermethylation by increasing gene transcription. Histone modifications are a type of epigenetic alteration that involves reversible chromatin rearrangements, which can have a dramatic effect on transcription without affecting the DNA sequence. As is well known, histones are the structural framework for eukaryotic chromosomes and provide three-dimensional architecture to the genome. Histone proteins are basic in nature and have four isoforms: H2A, H2B, H3, and H4. The N-terminal tails of histones are susceptible to various reversible covalent modifications including acetylation, methylation, phosphorylation, ubiquitination, and sumoylation [56–59]. Distinct histone modifications, such as histone 3 lysine 4 (H3K4) dimethylation and trimethylation and histone 3 lysine 27 (H3K27) acetylation at promoter regions and H3K4 monomethylation in enhancer regions of genes, are associated with active gene transcription. On the other hand, H3K9 and H3K27 dimethylation and trimethylation are involved in repressing promoter activity. Various histone tail modifications and associated enzymatic modifiers, such as histone methyltransferase (HMT) and histone deacetylase (HDAC), participate in epigenetic mechanisms that transduce active changes in gene transcription [61, 62]. The function of HMTs is to add methyl groups to lysine residues; on the other hand, histone demethylases (HMDs) remove methyl groups. There are separate HMTs and HDMs for various lysine residues, each with specific abilities to

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catalyze mono-, di-, or trimethylated states. Histone acetylation occurs most frequently on the lysine residues at H3 and H4 of the NH2-terminal. This is dynamically regulated by specific classes of enzymes known as histone acetyl transferases (HATs), which catalyze the addition of acetyl groups. HDACs catalyze the removal of acetyl groups from lysine residues in the NH2 terminal tails of histones. Primarily, increased histone acetylation causes the decondensation of chromatin and subsequent increase in the expression of genes, whereas lower acetylation leads to repression of chromatin and lower gene expression [63].

15.3.2 Epigenetic Modifications: Role in Psychiatric Disorders At the functional level, epigenetic processes are involved in both embryonic and postnatal neural development. Most importantly, they participate in neurogenesis [64], neuronal differentiation, cell survival [65], synaptic, and structural plasticity [65–67]. Earlier, it was believed that epigenetic marks obtained in utero remain identical throughout the adult life; however, it is now clear that epigenetic mechanisms are dynamically regulated and epigenetic remodeling takes place throughout the adult life. Because of the dynamic nature, epigenetic modifications are critically involved in susceptibility or resiliency to both internal and external cues. A large body of evidence shows that epigenetic modifications of genes are significantly involved in various psychiatric disorders, including major depressive disorder (MDD), schizophrenia, bipolar disorder (BD), and suicidal behavior [68–72]. DNA methylation and subsequent alteration in the expression of specific genes associated with GABAergic (GABAA α1), polyamine (SMS and SMOX and SAT1), neurotrophin (BDNF, TrkB, and TrkBT1), and stress (NR3C1, SKA2, and FKBP5) signaling have been shown in various stress-related disorders such as post-traumatic stress disorder, major depressive disorders, and suicidal behavior. In BD and schizophrenia, several studies showed downregulation of RELN and GAD67 genes, which were associated with hypermethylation of their respective promoter CPG islands (CGIs) [74]. Interestingly, hypermethylation of these genes were correlated with increased expression of DNA methyltransferase 1 (DNMT1) in cortical GABAergic interneurons [74–76]. A whole-genome DNA methylation study showed that epigenetic modifications can influence neurocognitive functions associated with suicidal behavior [78]. In this study, NR2E1, GRM7, CHRNB2, and DBH genes coding for membrane receptors and membrane-associated enzymes were correlated with hyperresponsive behavioral phenotypes and were considered risk factors for suicidal behavior. Astrocyte-specific genome-wide methylation study showed differentially methylated regions (DMRs) in the prefrontal cortex of patients who had died by suicide [79]. Interestingly, 90% of DMRs were associated with non-­ promoter regions and localized in the vicinity of gene body. Early-life adversity profoundly impacts gene transcription through epigenetic modifications [80, 81]. One study showed that epigenetic and transcriptomic alterations significantly affected oligodendrocytes in the gray matter of cingulate cortex of subjects with

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early life trauma and identified oligodendrocyte-specific epigenetic reprograming of POU3F1 and LINGO3 genes (Lutz, 2017). A twin study identified promoter hypermethylation of serotonin transporter gene SLC6A4 in bipolar patients [82]. In postmortem brain samples from BD patients, it has been shown that S/S genotype of HTTLPR was associated with promoter hypermethylation of SLC6A4, which led to the downregulation of its mRNA level. Methylation status of 5-HT3AR (5-hydroxytryptamine 3A) was also reported to mediate the effect of childhood trauma and its impact on adult psychopathology such as BD, borderline personality disorder, and attention deficit disorder [83]. Among various CpG sites, the methylation status of CpG2 III was found to be associated with the number of previous mood episodes, previous suicide attempts, and the polymorphism in single-­ nucleotide polymorphism rs1062613, regardless of underlying diagnosis. Recently, voltage-gated channel gene KCNQ3 gene, which has been the focus of genetic linkage studies [84, 85], showed significantly lower methylation level and correspondingly higher mRNA level in BD patients [86]. As far as histone modifications are concerned, HDAC4 mRNA showed increased expression in a depressed state of BD patients, whereas expression levels of HDAC6 and HDAC8 were decreased [87]. It has been reported that histone acetylation of CREB protein increases its transcription, which in turn, is involved in MDD and BD [88]. Another family of deacetylases, sirtuins, also target histone marks. The gene expression of sirtuin 1–7 [89] has been investigated in mood disorder patients. One study found state-dependent alterations in sirtuin 1, 2, and 6  in peripheral blood cells of BD and MDD patients [90]. The level of acetylated histone 3 (H3K9/K14ac) was investigated between a mixed patient sample from BD and schizophrenia, targeting psychosis candidate gene promoters. Acetylation levels of the mixed patients sample differed significantly to the controls [91]. Another postmortem study showed increased global histone H3 acetylation in BD subjects compared with controls [92]. A significant increase in type 3 histone (H3) lysine (K) methylation in the core octamer of nucleosomes close to the TRKB.T1 promoter was found, which was responsible for the downregulation of TRKB and TRKB.T1 in the brain of suicide subjects [93]. Both TRKB and TRKB.T1 play critical roles in neurotrophin signaling. An association of increased H3K4 trimethylation and higher risk of suicide has been reported [94]. Altogether, these studies suggest that the epigenetic modifications of genes can have far reaching impact on behavior associated with various psychiatric illnesses.

15.3.3 Epigenetic Pharmacotherapy Since epigenetic modifications can have significant behavioral consequences relevant to psychiatric illnesses, there has been an enormous interest in developing drugs that can specifically target individual molecules involved in epigenetic modifications. In addition, mechanisms of action of existing psychiatric drugs have been extensively examined for their association with epigenetic modifications; such

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examination not only provides their mechanisms of action but also offers novel targets for future drug development. Psychoactive Drugs and Their Epigenetic Effects  Valproic acid (VPA), a highly effective drug in BD, is one of most studied drug for its epigenetic targets [95]. The major function of VPA is to increase GABAergic activity by inhibiting GABA transaminase and blocking voltage-gated sodium channels. At the epigenetic level, VPA inhibits histone acetylation via interacting with HDACs, particularly HDAC class I and II, and increases the levels of acetylated histone H3 and H4, thereby stimulating gene expression [95–97]. VPA also interacts with HDAC2 and HDAC9; however, these actions are primarily effective in pain modulation [99] and preventing ischemic stroke [100], respectively. VPA can increase hippocampal neurogenesis, which is attributed to its increased histone acetylation activity [100–102]. VPA treatment also increases acetylation of H3 and H4 [74, 104] and decreases the expression of Dnmt1 and 3A and B, thereby increasing the expression of reelin (RELN) and glutamate decarboxylase (GAD), the two genes involved in BD and schizophrenia [105]. In cortical astrocytes and hippocampus, VPA increased the acetylation of histones H3 and H4 and decreased the levels of inhibitory H3K9 dimethylation. The increased acetylation and reduced DNA methylation were associated with increased expression of glutamate transporter-1 [106], a gene associated BD. Haloperidol, a widely used antipsychotic drug and D2 receptor antagonist, causes phosphorylation of histone H3 at serine 10, acetylation of H3K14, and phosphoacetylation [107]. Histone phosphoacetylation was also found to be associated with raclopride, another D2 receptor blocker [108]. Striatal H3 phosphorylation, in response to haloperidol, has also been reported. Interestingly, a benzamine derivate, MS-275 ((pyridin-3-ylmethyl N-[[4 [(2aminophenyl)carbamoyl]phenyl]methyl]carbamate)), acts as HDAC inhibitor and is highly effective in increasing the acetylation of H3 associated with Reelin and GAD67 gene promoters [109]. Interestingly, MS-275 was much more potent than VPA in increasing acetylhistone 3 (Ac-H3), suggesting that this benzamine derivative may have greater efficacy when used adjunctive to antipsychotics [109]. Another benzamine derivative, sulpiride, increased H3K9 and H3K14 acetylation in the promoter region of reelin gene [109]. Risperidone, an antipsychotic, can induce global phosphoacetylation of H3 in the striatum [107]. Fluoxetine, an antidepressant, decreases histone H3K9 trimethylation induced by chronic restraint stress [110]. In serotonin projection areas, fluoxetine induced expression of MBD1 and Mecp2 transcripts [111]. Induction of the MBD proteins was accompanied with enhanced HDAC2 labeling intensity and mRNA synthesis [111]. Antidepressants can also reverse repressive histone modification patterns to elevate Bdnf expression, a gene involved in stress, mood disorders, and the mechanisms of action of antidepressants [112]. For example, escitalopram reduces HDAC expression, thereby increasing the acetylation of histones in mice which were previously exposed to maternal stress. Maternal stress reduces H3 and H4 acetylation at BDNF promoter IV, whereas escitalopram reduces depressive behavior by increasing acetylation and causing subsequent increase in

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BDNF exon IV expression. Antidepressant treatment can also modify patterns of histone modifications to elevate BDNF expression [113]. Imipramine treatment reduces HDAC5 expression and elevates H3 and H4 acetylation, which leads to the alleviation of anxiety-like behavior [114]. Amitriptyline, another antidepressant drug, induces cytosine demethylation, along with a reduction in the enzymatic activity of DNMT. Drugs Targeting Specific Epigenetic Pathways and Their Potential in the Treatment of Psychiatric Disorders  Several drugs that are involved in epigenetic processes are being developed for various disorders including psychiatric disorders. Some of these drugs have been tested in an animal model, and some are still in the conceptual phase; however, the development of these drugs is exciting and may have the potential to provide personalized treatment for psychiatric illnesses. Sodium butyrate is a widely used HDAC inhibitor that exerts antidepressant-like effects [115]. It has been shown that sodium butyrate can upregulate both BDNF and GDNF genes in astrocytes via histone H3 acetylation in the promoter regions of these genes [116]. In mice, it has shown high efficiency in enhancing long-term memory and memory formation, which was primarily driven by elevation in trimethylation and simultaneous diminution of dimethylation of H3K9 [117]. Also, in the genetically depressed mice, which show lower levels of 10–11 translocation methyl cytosine dioxygenase 1 (TET1), sodium butyrate not only exhibited antidepressant activity but also increased levels of TET1. TET1 upregulation was accompanied by decrease in methylation and increase in hydroxymethylation of Bdnf gene [118]. TET1 catalyzes the conversion of DNA methylation to hydroxymethylation. Interestingly, combined treatment with sodium butyrate and fluoxetine was superior to fluoxetine alone. Thus, the combination of a HDAC inhibitor together with an SSRI might be a promising novel antidepressant treatment strategy. Trichostatin A (TSA; 7-[4-(dimethylamino) phenyl]-N-hydroxy-4,6-dimethyl-7-oxohepta-2,4-­ dienamide) is an HDAC inhibitor and targets classes I and II HDACs [119]. TSA show differential effects on two activation dependent regions of the Bdnf gene physically linked to transcription sites for exons I and IV. TSA treatment of cultures of hippocampal neurons produced a stronger response at promoter 1, which was correlated with increased occupancy of the promoter by acetylated histones (H3AcK9/ K14). TSA treatment also produced a time-dependent increase in the level of H3AcK9 and H3AcK14 protein and HDAC1 mRNA levels and HDAC1 protein levels. These results suggest that the inhibition of HDAC activity by TSA activates BDNF transcription and a compensatory change in HDAC1 expression in neurons. TSA also increased the expression of GDNF along with GDNF promoter activity and promoter-associated H3 acetylation [116]. Interestingly, TSA treatment reversed the adverse early life experience induced by poor maternal care [120]. TSA was also effective in regulating GAD67, RELN, and GLET-1 genes through demethylation and acetylation [74, 104, 121, 122]. HDAC inhibitors such as sirtinol (2-[(2-hydroxynaphthalen-1-ylmethylene)amino]-N-(1-phenethyl)benzamide) and MS-275 have also been investigated as potential antidepressants in a rodent model [123]. To date, no clinical studies have been conducted to evaluate the effect of

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newly designed HDAC inhibitors in psychiatric patients. L-Methylfolate as methyl donor has been tested as an adjunctive therapy in several clinical trials [124] and has been found to be safe and effective in MDD patients [125]. Another methyl donor, S-adenosyl methionine ((2S)-2-amino-4-[[(2S,3S,4R,5R)-5-(6-aminopurin-9-yl)3,4-dihydroxy oxolan-2-yl]methyl-methyl sulfonio]butanoate), has been shown to restore normal gene expression in neuroblastoma cells [126]. It has also been demonstrated that methionine administration increases the methylation levels of GAD67 and RELN with a consequent downregulation of their corresponding mRNAs. In clinical trials, SAMe was not different from placebo and established antidepressants; the exception was that compared to imipramine, fewer participants experienced adverse effects when treated with parenteral SAMe [127]. One of the shortcomings of global epigenetic modifiers is their broad effect on the epigenome. Also, epigenetic changes are tissue and cell-type specific. Recent developments in finding effective epigenetic targets revolve around epigenome manipulation at specified loci. The purpose of this approach is to adjust only the specific pathogenic marks rather than altering the entire epigenome. This new technique is based on generating targeted EpiEffectors, which are engineered transcription factors such as transcription activator-like effectors or zinc-finger-proteins, which have been designed to bind at specific loci in the genome [128]. Using this approach, studies have shown locus-specific epigenetic remodeling and its impact on correcting addiction and depression-related behaviors [129]. In addition, engineered zinc finger protein activator of endogenous glial cell line-derived neurotrophic factor gene provided functional neuroprotection in a rat model of Parkinson’s disease [130]. CRISPR-dCas9 is another highly promising strategy, which facilitates the design of DNA recognition domains. Recent studies suggest the usefulness of this strategy in both in vitro and in animals where it induced long-lasting changes in DNA methylation [130–132] or histone modifications [134, 135]. Through the use of another innovative approach, a recent study demonstrated that fusion of Tet1 or Dnmt3a with a catalytically inactive Cas9 enabled targeted DNA methylation editing of Bdnf gene in a long-lasting manner [136]. These techniques can be highly effective in delivering enduring epigenetic marks that will be crucial in the patient population.

15.4 Conclusion The decoding of the human genome has been truly revolutionary, ushering in a new era of drug development. The association of specific gene variants with human diseases has allowed the identification of disease risk and provided some targets for new therapies. Specific examples include BRCA1/2 and ERBB2 (HER2) variants in breast cancer. However, most human illnesses are not single-gene diseases; most are complex disease traits that not only can involve contributions from many genes but also have significant environmental components. Examples of diseases that have

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some underlying biological (presumably genetic) predisposing factors and also strong environmental influences include such common conditions as not only hypertension and type 2 diabetes but also depression, post-traumatic stress disorder, and schizophrenia. These complex diseases are not amenable to treatment development that target abnormalities in single-gene sequences (i.e., the gene product itself or downstream effects). Epigenetics has emerged as an important potential target of treatment development given the important role of the environment in disease pathogenesis. It remains to be seen if epigenetic changes will emerge as bona fide treatment targets. However, the development of molecular approaches that target specific epigenetic marks may ultimately treat specific environmentally induced disease. However, this approach may also be able to improve a broad set of disorders that are affected by similar environmental antecedents. As an example, early life trauma induces DNA methylation [137], and it predisposes to the subsequent development of separate disorders such as depression [138], PTSD [139], and suicide [140]. The epigenetic changes may serve as common and possibly modifiable vulnerability factors for trauma-related disorders more broadly. Targeting these changes might lead to novel treatments and, more importantly, ways of reversing the effects of early life stress, thereby reducing risk for a range of mental disorders. This could bring a new generation of risk modifying approaches that may provide ways of preventing and not just treating diseases.

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Chapter 16

Increased Inflammation and Treatment of Depression: From Resistance to Reuse, Repurposing, and Redesign Jennifer C. Felger

Abstract  Based on mounting clinical and translational evidence demonstrating the impact of exogenously administered inflammatory stimuli on the brain and behavior, increased endogenous inflammation has received attention as one pathophysiologic process contributing to psychiatric illnesses and particularly depression. Increased endogenous inflammation is observed in a significant proportion of depressed patients and has been associated with reduced responsiveness to standard antidepressant therapies. This chapter presents recent evidence that inflammation affects neurotransmitters and neurocircuits to contribute to specific depressive symptoms including anhedonia, motor slowing, and anxiety, which may preferentially improve after anti-cytokine therapies in patients with evidence of increased inflammation. Existing and novel pharmacological strategies that target inflammation or its downstream effects on the brain and behavior will be discussed in the context of a need for intelligent trial design in order to meaningfully translate these concepts and develop more precise therapies for depressed patients with increased inflammation. Keywords  Inflammation · Cytokines · Depression · Anhedonia · Dopamine · Glutamate · Antidepressants

16.1 Introduction Based on mounting clinical and translational evidence demonstrating the impact of exogenously administered inflammatory stimuli on the brain and behavior, increased endogenous inflammation has received attention as a pathophysiologic process that may contribute to psychiatric illnesses and particularly depression. A rich literature describes increased inflammation in patients with depression and other psychiatric J. C. Felger (*) Emory University School of Medicine, Atlanta, GA, USA e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 M. Macaluso et al. (eds.), Drug Development in Psychiatry, Advances in Neurobiology 30, https://doi.org/10.1007/978-3-031-21054-9_16

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disorders, as evidenced by elevated peripheral and central inflammatory cytokines and acute phase proteins. This endogenous inflammation may arise from numerous sources including risk factors for psychiatric illness (e.g., stress, obesity or metabolic dysfunction, genetics, and lifestyle factors) and has been associated with reduced responsiveness to standard antidepressant therapies. As both increased inflammation and treatment resistance occur in a significant proportion of patients with major depressive disorder (MDD), new conceptual frameworks are needed to identify relevant targets and develop novel therapies. This chapter will present recent evidence that inflammation affects neurotransmitters and neurocircuits to contribute to specific depressive symptoms including anhedonia and motor retardation. Converging findings from neuroimaging studies involving the administration of exogenous inflammatory stimuli or characterization of depressed patients with increased endogenous inflammation will be discussed in relation to growing evidence that inhibition of inflammation with anti-cytokine therapies in patient with mood disorder including depression specifically reduces anhedonia in patients with evidence of increased inflammation. This chapter will then focus on potential pharmacological strategies based on the neurobiological mechanisms by which inflammation affects neurotransmitters, circuits, and symptoms. Such strategies include the use of existing compounds, either by employing biomarkers to guide selection of antidepressants for patients with high inflammation or by repurposing of existing compounds indicated for other conditions as novel therapies to target inflammation or its downstream effects on the brain and behavior. The need for novel immune-modulatory or redesigned, next-generation anti-­ cytokine therapies will also be discussed in light of design considerations for clinical trials that are required to meaningfully translate these concepts and develop more precise therapies for patients with increased inflammation.

16.2 Increased Inflammation in Depression: Sources, Symptoms, and Role in Treatment Resistance 16.2.1 Inflammation in Depression: Causes and Consequences Numerous studies including meta-analyses have reported increased peripheral and central inflammatory markers like the acute phase reactant, C-reactive protein (CRP) and the inflammatory cytokines interleukin (IL)-1, IL-6, and tumor necrosis factor (TNF), in MDD [1–4]. Longitudinal studies have also found that increased inflammatory markers predicted subsequent depression symptoms [5–7], even above and beyond prior depression severity [8]. Of note, similar increases in inflammatory markers have been described in other psychiatric disorders that share commons symptom domains like anhedonia, motor slowing, and anxiety, including

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bipolar disorder, schizophrenia, anxiety disorders, and post-traumatic stress disorder (PTSD) [9–12]. In addition inflammation-related genetic risk [13], gene expression in peripheral blood immune cells of MDD patients have also revealed activation of oxidative stress pathways and inflammatory cytokines as well as canonical inflammatory signaling pathways including toll-like receptors, nuclear factor kappa B, and the NLRP3 inflammasome complex [14–18]. Activation of these pathways reflects innate immune responses to both pathogen-associated molecular patterns and danger-associated molecular patterns that are generated by host cells under stress, including psychological stress [19]. Indeed, in MDD patients who are otherwise medically healthy, genetic predisposition may interact with not only stress and trauma but also a range of environmental and lifestyle factors to activate the innate immune system and contribute to low-grade systemic “sterile” inflammation in the absence of pathogens including disturbed sleep, physical inactivity, obesity and metabolic disturbances, Western diet, aging, and smoking [20]. Many of these causes of inflammation are risk also factors for both psychiatric and major medical illnesses, suggesting shared pathophysiologic processes that may explain notable comorbidity between psychiatric disorders and cardiovascular disease, diabetes, and cancer [21]. While most studies report relationships between increased peripheral inflammatory markers and depression and many sources of inflammation per above are from the body, inflammatory cytokines and activated immune cells can access the CNS to directly influence neurotransmitters and circuits and to activate local inflammatory processes. Increased inflammatory markers have been described in the cerebrospinal fluid (CSF) in MDD [22, 23]. Postmortem studies have identified evidence of increased inflammatory signaling in brain parenchyma, including increased TLR expression, expression of inflammatory cytokines, and evidence of both peripheral immune cell trafficking to the brain and activation of microglia [24–27]. Positron emission tomography (PET) imaging of increased translocator protein (TSPO), which is thought to reflect activated microglia and macrophage, has also been reported throughout the brain in MDD but did not relate to peripheral inflammatory markers [28]. While TSPO binds activated microglia in response to acute inflammation [29], it is not clear whether this is specific to inflammatory microglia versus those that activated to perform physiologic roles like synaptic pruning, how much of the signal is due to binding to other cells including astrocytes and neurons [30], or whether signal is confounded by uptake in the periphery of patients with increased inflammation [31] in MDD. It should be noted however that recent data show that inflammatory pathways can disrupt the blood brain barrier (BBB) in discrete subcortical brain regions, particularly those that regulate motivation and reward [32] and correspond to the impact of inflammation on specific circuits and symptoms, as detailed below.

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16.2.2 Increased Inflammation and Antidepressant Treatment Response Whereas not every patient with MDD has increased inflammation, higher concentrations of inflammatory markers have been reliably observed in patients with reduced responsiveness to conventional antidepressants [33]. Indeed, approximately 25–40% of MDD patients depending on the sample exhibit CRP >3 mg/L, considered high risk for developing cardiovascular disease per American Heart Association guidelines [3, 4, 34, 35], with even more falling in the moderate risk range of CRP 1–3 mg/L, while 1 mg/L prior to therapy are less responsive to antidepressants, especially not only selective serotonin reuptake inhibitors (SSRIs) but also serotonin norepinephrine reuptake inhibitors (SNRIs), over the course of an adequate trial [35–38]. Measurement of inflammatory cytokine mRNA expression in peripheral immune cells was even more predictive of this effect than CRP [37, 39]. Similarly, in MDD patients with a history of antidepressant nonresponse, higher levels of inflammatory markers including IL-6, TNF, and its soluble receptor 2 and CRP were associated with increasing number of prior failed trials [40, 41]. Moreover, some studies have found that patients with CRP >1 mg/L are more responsive to drugs that affect dopaminergic and noradrenergic pathways including bupropion and nortriptyline [35, 42]. Additionally, MDD patients with higher levels of inflammatory markers have shown better response to adjuvant or therapies that boost monoamine availability or target glutamate [42–44] and also electroconvulsive therapy [45]. Together, these data suggest that (1) inflammatory markers may help guide antidepressant treatment selection and (2) better understanding the mechanisms by which inflammation affects the brain may lead to development of novel therapies targeted to the many MDD patients with higher levels of inflammation. Therefore, it is it is important to prospectively consider the role of inflammation in future antidepressant trials and to design studies examining novel treatment avenues using appropriately selected biomarkers and outcome measures relevant to specific symptoms associated with high inflammation in MDD.

16.2.3 Relationships Between Inflammation and Symptom Domains Consistent with impact of inflammatory cytokines on specific circuits and symptoms as described below, evidence of increased inflammation in MDD has been associated with specific symptoms that are common to other disorders including anhedonia, motor slowing, and anxiety [46–49]. For example, our group recently identified clusters of cytokines and their soluble receptors in CSF that were associated with higher levels of plasma CRP in otherwise medically stable patients with MDD [4]. These CSF markers, in turn, associated with symptom severity with the

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strongest relationships between CSF TNF and reduced motivation per a subscale from the Multidimensional Fatigue Inventory and CSF IL-6 soluble receptor and anhedonia per a subscale from the Inventory of Depressive Symptomatology Self-­ Report (IDS-SR) that correlates with the both the self and clinician-administered Snaith-Hamilton pleasure scale (SHAPS) [50, 51]. These results were confirmed and extended by a study demonstrating that both T- and non-T-cell cytokines were associated with anhedonia severity per the IDS-SR subscale [52]. Furthermore, longitudinal associations between cytokines and anhedonia have been reported in MDD where higher baseline plasma TNF predicted greater severity of anhedonia both at baseline and at a four-month follow-up [53]. Similar relationships between psychomotor slowing and inflammatory markers have also been observed in MMD [54], and many studies have found associations between increased inflammatory markers in schizophrenia and negative symptoms, which include motivational deficits, blunted affect, and social withdrawal among others [55]. In regard to anxiety, a growing literature reports correlations between increased CRP and inflammatory cytokines and symptoms of anxiety [46, 56], including in a longitudinal study [57] and in patients with MDD [58]. Together, these studies provide a clinical framework for the potential role of inflammation in symptoms of anhedonia, motor slowing and anxiety in MDD, and other psychiatric disorders and support the need for mechanistic studies to better understand the impact of inflammation on the brain.

16.2.4 Inhibition of Inflammation in Depression and Symptom Specificity Numerous studies treating psychiatric patients with rather nonspecific anti-­ inflammatory agents having multiple off-target effects, e.g., nonsteroidal anti-­ inflammatory drugs and minocycline [59–61], were not targeted to patients with increased inflammation and yield mixed results. Although having limited viability as antidepressants for a myriad of reasons [62, 63], more specific anti-cytokine therapies have shown efficacy for reducing specific depressive symptoms in depressed or medically ill patients with high inflammation. For example, treatment of patients with autoimmune or inflammatory disorders with anti-cytokine therapies reduces depression symptom severity [64]. The TNF antagonist infliximab reduced depression severity with respect to placebo in treatment-resistant MDD patients with higher concentrations of plasma CRP, and anhedonia (work and activities) was the most improved symptom followed by motor slowing (retardation) and anxiety (psychic anxiety) [3]. Moreover, similar results have been seen in two recent studies reporting that anti-TNF or IL-6 therapies in unipolar or bipolar depressed patients with evidence of increased inflammation were primarily effective in reducing anhedonia assessed by SHAPS [3, 65, 66]. These data reinforce specificity for the effects of inflammation on neurobiological pathways that contribute to anhedonia, as well as motor slowing and anxiety, as discussed below.

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16.3 Inflammation Effects on the Brain and Behavior Neuroimaging studies have consistently found that administration of a variety of peripheral inflammatory stimuli, including cytokines and cytokine inducers (e.g., vaccination and subfebrile doses of endotoxin), impact corticostriatal reward and motor circuits to drive reduced motivation and motor slowing as well as anxiety-­ related brain regions including amygdala, insula, and anterior cingulate cortex (ACC), which may result from cytokine effects on monoamines and glutamate (Fig. 16.1) [67]. Causal evidence for the effects of inflammation on neural circuits and neurotransmitters were initially revealed in patients administered chronic inflammatory cytokines, such as the antiviral and antiproliferative cytokine interferon (IFN)-α, which caused clinical depression in up to half and depressive symptoms in nearly all patients over weeks to months of treatment for infectious diseases or cancer [68, 69]. Like IFN-α, endotoxin and vaccination induce release of classic inflammatory cytokines IL-6, IL-1, and TNF in association with transient increases

Fig. 16.1  Mechanisms of inflammation effects on the brain and behavior and targets for intervention in depression. Inflammation is increased in otherwise medically stable patients with major depressive disorder (MDD) due to environmental exposures, genetics, psychosocial stressors, diet, and other lifestyle factors. Innate immune cell activation and the release of inflammatory cytokines cause both increased CRP production from the liver and effects on brain neurotransmitters and circuits to drive relevant behavioral changes. Evidence indicates that inflammation and cytokines may preferentially affects dopamine and glutamate systems to disrupt circuits involved in reward and motor activity, as well as those involved anxiety and emotional regulation. In terms of potential novel therapies that may target inflammation or its effects on the brain, there is current interest in (1) compounds that increase dopamine or decrease glutamate signaling, (2) therapies that directly target the immune system to decrease inflammation, and (3) alternative strategies via lifestyle changes or treatments that modify the sources of inflammation. CRP C-reactive protein, dACC dorsal anterior cingulate cortex, DMF dimethyl fumarate, FMT fecal microbiota transplant, IDO indoleamine 2,3 dioxygenase, L-DOPA levodopa, NAC N-acetyl cysteine, NMDA n-methyl-d-­ aspartate, P2X7 purinergic ATP receptor 7, SAMe S-adenosylmethionine, vmPFC ventromedial prefrontal cortex

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in depressive symptoms and are commonly used in lab settings to understand their acute effects on the brain [70], as reviewed below. Recent work has also translated findings from these studies investigating causal effects of exogenously administered inflammatory stimuli to study relationships between endogenous inflammation, neurotransmitters, and circuits in MDD patients.

16.3.1 Impact of Inflammation on Reward and Motor Regions and Circuits Early positron emission tomography (PET) studies investigating broad effects of chronic inflammatory cytokines on the brain found that resting glucose metabolism was increased in basal ganglia and decreased in frontal cortex [71, 72], whereby increased metabolism in the left putamen and left nucleus accumbens correlated with IFN-α-induced anergia and fatigue [71]. This pattern of increased glucose metabolism in basal ganglia nuclei is similar to that seen in patients with Parkinson’s disease (PD) [73], which thought to indicate increased oscillatory burst activity secondary to loss of inhibitory dopamine input [74]. Complementary PET using radio-­ labeled dopamine precursor, [18F]fluorodopa, in IFN-α-treated patients also showed both increased uptake and decreased turnover of FDOPA, reflecting decreased availability of dopamine/precursor and impaired packaging or release of newly synthesized dopamine, in the caudate, putamen, and VS [68]. Magnetic resonance spectroscopy (MRS) further showed increased glutamate in left basal ganglia in patients treated with IFN-α that correlated with reduced motivation [75]. Complementary to these chronic studies, acute challenge with IFN-α caused rapid (4 hours) changes in striatal microstructure that predicted subsequent development of fatigue [76, 77]. Functional impact of the effects of peripheral inflammation on brain regions relevant to reduced motivation and motor activity and involving dopamine and glutamate have also been revealed by functional MRI (fMRI). Indeed, decreased ventral striatal (VS) neural activation to win versus loss was seen in a gambling task after chronic IFN-α, which correlated with self-reported reduced motivation [68]. Studies in healthy controls using vaccination and subfebrile doses of endotoxin have also assessed acute effects of inflammation on reward processing. Reduced activation of VS to reward-predicting cues during a monetary incentive delay task (MIDT) were associated with increased self-reported depressed mood [78] and with cytokine responses in women but not men hours after endotoxin [79]. In a probabilistic instrumental learning task combined with fMRI, typhoid vaccine compared with saline control reduced behavioral attractiveness of rewards while making punishments more aversive, in association with opposing change in VS responses that were decreased to positive feedback but increased to negative feedback [80]. This corresponds with a study showing that greater inflammatory responses to laboratory stress correlated with decreased VS sensitivity to positive feedback [81]. Additionally, typhoid vaccination affected task-based activity in the substantia nigra

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that correlated with both psychomotor slowing and increased peripheral blood concentrations of IL-6 [82, 83]. Finally, acute administration of IFN-α or typhoid vaccination has been shown to acutely decrease functional connectivity (FC) within motivation-relevant brain regions including VS and the ventromedial prefrontal cortex (vmPFC) [84, 85].

16.3.2 Impact of Inflammation on Regions and Circuits for Fear, Anxiety, and Emotional Processing Similar to reports of increased reactivity in MDD as well as anxiety disorders and PTSD, exogenous administration of peripheral inflammatory stimuli has been shown to increase neural activity in amygdala, dorsal ACC, and insula [86]. For example, acute IFN-α (4 hour) administration enhanced right amygdala responses to sad versus neutral faces, which correlated with subsequent IFN-α-induced depression severity [87]. Increased IL-6 and TNF after administration of endotoxin to healthy subjects was also shown to increase amygdala activity in response to socially threatening images, which correlated with feelings of social disconnection [88]. Greater dorsal ACC activation was also seen in IFN-α -treated patients that highly correlated with task-related errors [89], and this may be due to increased glutamate in dorsal ACC as measured by MRS in patients administered IFN-a that correlated with depressive symptom severity [90]. In participants administered endotoxin prior to a neuroimaging session in which they were socially excluded during a virtual ball-tossing game, increases in IL-6 were associated with increases in social pain-­ related neural activity in both dorsal ACC and anterior insula in females but not males [91]. Another study administering typhoid vaccination also reported increased activation of amygdala and dorsal ACC as well as insula, during presentation of congruent and incongruent stimuli [92]. Given the role of the insula in interoception, it is not surprising that this brain region also had increased resting glucose metabolism as measured by PET after endotoxin [93]. These findings suggest that increased inflammatory cytokines in the periphery may contribute to altered neural activity in circuits involving amygdala, dorsal ACC, and insula to disrupt emotional processing in MDD and anxiety-related disorders.

16.3.3 Endogenous Inflammation and Circuit Dysfunction in Patients with Depression In light of converging evidence of the impact of exogenously induced inflammation on circuits and symptoms relevant to reduced motivation, motor slowing, and anxiety (as described above), recent studies have examined a potential role for increased endogenous inflammation in relevant circuit deficits that are frequently observed in

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patients with MDD and other psychiatric disorders [94–96]. For example, in medically stable and unmedicated MDD patients, endogenous inflammation as measured by plasma CRP and inflammatory cytokines was associated with lower left VS to vmPFC FC, which in turn positively correlated with anhedonia per the IDS-SR subscale [51]. These targeted findings were corroborated by parcellation-based network analysis in MDD revealing vmPFC and VS (a region parcellated as anterior ventral caudate) as the two most significant hubs, respectively, in a widely distributed network of low FC within 63 features in relation to CRP, subsets of which were highly predictive of anhedonia as measured by the IDS-SR subscale and SHAPS [97]. Of note, relationships between increased inflammation and low FC among several regions, dorsal striatal regions, the vmPFC and pre-supplementary motor area, and key components of corticostriatal circuitry involved in linking motivation to motor output [98, 99], were correlated with objective measures of psychomotor slowing in these studies [51, 97]. Furthermore, FC was shown to mediate relationships between CRP and anhedonia and psychomotor symptom severity [51]. Similar relationships between increased inflammation and low FC in primarily left VS to vmPFC reward circuitry were also observed in treatment-resistant MDD patients [100] and in trauma-exposed women in relation to an anhedonia subscale via Beck Depression Inventory [101]. Further evidence of associations between increased endogenous inflammation and functional changes in reward circuits include reduced striatal activation during reward anticipation in MDD patients with higher CRP and inflammatory cytokines [102, 103]. While the above findings generally indicate a role for reduced dopamine signaling, high inflammation in MDD was associated with increased glutamate concentrations in left basal ganglia that correlated with anhedonia [104]. Patients with combined elevations in CRP and glutamate displayed both high anhedonia and low regional homogeneity in left basal ganglia, indicating disrupted local coherence of activity that may be driven by increased glutamate [105]. Regarding threat and anxiety-related circuitry, inflammatory markers have been associated with similar deficits in amygdala-vmPFC circuitry as those reported to characterize individuals with high anxiety, MDD, and/or PTSD [106–108]. For example, we previously found that higher concentrations of plasma CRP and inflammatory cytokines correlated with lower right amygdala-vmPFC FC in patients with a primary diagnosis of MDD in association with anxiety symptoms, particularly in patients with comorbid anxiety-related disorders including PTSD [109]. Recent studies in adolescents have also found relationships between endogenous inflammation and altered FC in circuits relevant to threat, anxiety, and emotional processing [110, 111]. Interestingly, acute blockade of TNF in inflammatory arthritis patients with infliximab decreased right amygdala reactivity to emotional (sad, happy, and neutral) faces in association with reduced depressive symptoms at 24 hours [87], suggesting emotional reactivity as a potential target for efficacy of anti-­inflammatory therapies.

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16.4 Treatment Targets for Depressed Patients with Increased Inflammation Given the mounting evidence of differential response to antidepressants in MDD patients with higher versus lower levels of inflammation and the reproducible effects of inflammation on behavior, there is a need to consider inflammation in studies examining antidepressant outcomes and for development of novel therapies that block inflammation or its consequences on the brain (Fig. 16.1). Numerous clinical trials have addressed this concern by the use of agents with putative anti-inflammatory activity as adjuvant or therapy in patients with psychiatric disorders, primarily in depression or schizophrenia [112–114]. Meta-analyses of the use of such drugs including cyclooxygenase (COX)-2 inhibitors, anti-cytokine therapies, minocycline, statins, pioglitazone, glucocorticoids, and omega-3 fatty acids suggest modest efficacy [60, 113–117] despite small sample sizes, heterogeneity across studies, and numerous design issues. Most studies used therapies as adjuvant to conventional antidepressants and did compare with placebo, patients were rarely selected to have high inflammation, only a few studies measured inflammatory markers to stratify patients or establish anti-inflammatory effect, and importantly, many of the chosen therapies convey only mild anti-inflammatory activity in the context of numerous “off target” effects that can confound data interpretation [63, 118]. In the largest randomized controlled trial to date using the COX-2 inhibitor celecoxib and minocycline (an antibiotic thought to stabilize microglia but also disrupt microbiota [119]), both failed to separate from placebo in reducing depressive symptoms in depressed bipolar patients [61]. Two studies did, however, consider inflammation levels in treatment-resistant or bipolar depression and found that higher CRP (>3 mg/L) or IL-6 concentrations prior to treatment were predictive of response to minocycline [120, 121], with reduced serum IL-6 after treatment seen only in bipolar depressed responders [121]. While existing cytokine antagonists may not be viable antidepressants [62, 63], they have demonstrated efficacy in depressed patients with high inflammation with specificity for symptoms consistent with the known effects of inflammation on the brain [3, 65, 66], thus providing a foundation for enrolment and outcomes strategies for testing novel therapies. Given the above-described inconsistencies and challenges in studying anti-­ inflammatory therapies for depression, existing or novel compounds that target the neurotransmitters impacted by inflammation, like dopamine and glutamate, may serve as more proximal approaches for translating these concepts into patients (Fig. 16.1(1)). Discussed below are the multiple pharmacological interventions that can be used to block inflammation or its downstream effects on the brain, starting with the potential for informed selection of available antidepressants and reuse or repurposing of existing compounds that affect neurotransmitters. Because the above-described use of COX-2 inhibitors, anti-cytokine therapies, minocycline, fatty acids, and the like have been reviewed extensively elsewhere, discussion on immune targets will focus on novel agents or redesign of existing therapies (Fig. 16.1(2)), along with mention of alternative treatments that may exert efficacy

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via effects on neural and physiologic processes that modulate inflammation (Fig. 16.1(3)). Biomarker and study design considerations for patient selection and target engagement of the brain and behavior will also be discussed.

16.4.1 Compounds That Increase Dopamine Synthesis, Synaptic Availability, and Receptor Signaling Dopamine reuptake  Decreased response to conventional antidepressant therapies like SSRIs in patients with high inflammation may be due to decreased monoamine synthesis and availability, or to facilitatory effects of cytokines on serotonin transporters, which may circumvent or interfere with their action [122, 123]. Alternatively, reduced response may be due to a preferential access and effects of peripheral inflammation on reward and motor-related brain regions that receive primarily dopamine input [67, 124], consistent with evidence of increased responsiveness in these patients to antidepressants with catecholamine activity and particularly bupropion [42]. Bupropion, an FDA approved and effective medication for MDD [125] that functions primarily by inhibiting dopamine and norepinephrine reuptake, has been shown to increase high effort activity in rats [126]. Some trials also suggest preferential response of anhedonia to bupropion [127, 128]. Together, these findings warranted further investigation of potential efficacy in MDD with high inflammation, such as a recent trial prospectively examining the ability of bupropion versus escitalopram to increase FC in reward circuitry and improve motivation in patients with high CRP (NCT04352101). It should be noted that although classical psychostimulant medications with potent effects on dopamine reuptake or release increase motivation in rodent models and acutely in healthy humans [126, 129, 130], they have demonstrated only limited efficacy in chronically treating fatigue and other dopamine-related symptoms in trials for patients with cancer and other medical illnesses that are associated with inflammation [131–140], or as augmentation therapy for depression [141–145]. Dopamine synthesis  While compounds that inhibit dopamine reuptake may exert efficacy in high inflammation patients, the primary mechanisms of inflammation effects are likely through the inhibition of key components of dopamine synthesis like tetrahydrobiopterin (BH4) [146, 147], a pivotal cofactor for the enzymes that synthesize dopamine and other monoamines. Indeed,  inflammation reduces BH4 availability through oxidation and excessive conversion to BH2 during generation of nitric oxide by nitric oxide synthase [148]. Therefore, depressed patients with high inflammation may benefit from therapies that increase BH4 stability or activity including sapropterin and folic acid, L-methylfolate, and S-adenosylmethionine (SAMe). Low serum folate has been associated with increased risk of depression and non-response to antidepressant treatment and an increased likelihood of depression relapse [149], yet clinical trials using L-methylfolate (marketed as Deplin and Zervalx) and SAMe have shown mixed results [150, 151]. Post hoc analysis of two

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parallel-sequential adjuvant trials of L-methylfolate in patients with MDD [150] did however reveal that a combination of increased concentrations of leptin, CRP, and inflammatory cytokines or high BMI was associated with greater symptom improvement [44], supporting potential value of targeting such therapies to MDD patients with high inflammation. Another strategy to address impaired dopamine synthesis is the administration of its precursor, levodopa (L-DOPA). Indeed, in monkeys experiencing similar behavioral responses including reduced effort-based sucrose consumption after chronic IFN-α exposure [152], decreases in striatal dopamine release were reversed by L-DOPA administered via reverse in  vivo microdialysis [153]. Replacement of dopamine with L-DOPA improves motor function and was also shown to increase motivation in patients with PD [154]. Whether L-DOPA (in combination with carbidopa) versus placebo improves FC in reward circuitry in association with improved motivation and anhedonia in MDD patients with higher levels of CRP is currently being studied (NCT04723147). Open-label L-DOPA-carbidopa administration to aged depressed patients with motor slowing, a group likely to exhibit increased inflammation, also showed a positive antidepressant response [155], and a similar ongoing study in this population aims to better understand mechanisms of these findings including the potential role of inflammation (NCT04469959). Dopamine agonists  Dopamine receptor agonists have received attention as efficacious augmentation strategies for depression. For example, antiparkinsonian agents like pramipexole have demonstrated efficacy to reduce depressive symptoms in patients with treatment-resistant depression [156–159]. Although it is unknown whether this effect is specific to high inflammation in depressed patients [160], it has been shown to block endotoxin-induced degeneration of nigrostriatal dopamine cells in rodents [161]. A growing body of evidence also supports the use of atypical antipsychotics as an augmentation strategy in MDD, including meta-analyses suggesting these agents are more effective than placebo for both response and remission [162, 163]. In addition to more serotonergic activity, newer generation antipsychotics like aripiprazole and amisulpride appear to act as D2/3 partial agonists by facilitate dopamine signaling at lower doses or in states of low endogenous ligand [164], such as with increased inflammation, while preventing overstimulation when endogenous dopamine levels are high.

16.4.2 Therapies That Target Glutamate Transmission Modulation of the kynurenine pathway  Immune-mediated activation of indoleamine 2,3 dioxygenase (IDO) catabolizes tryptophan (TRP), the primary amino-­ acid precursor of serotonin, to kynurenine (KYN), downstream metabolites of which affect glutamate transmission in the brain [165, 166]. Peripheral blood KYN/

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TRP ratio in combination with TNF defines a population of MDD patients with increased anhedonia and treatment resistance [167]. With regard to preventing activation of the KYN pathway, the IDO antagonist, 1-methyl tryptophan (1-MT) has been shown to abrogate depressive-like behavior in animal models of inflammatory challenge or infection [168, 169]. Given the importance of serotonin in T-cell activation, there has been interest in developing IDO inhibitors as a pharmacologic strategy to enhance T-cell function against cancer [170], but compounds like 1-MT have not yet been translated outside of oncology. As leucine competes with KYN for the large amino acid transporter, it can inhibit transport of KYN into the brain and reduce production of neuroactive metabolites like quinolinic acid (QUIN) from KYN in microglia [171]. Thus, high dose leucine (8 mg/d for 2 weeks) is currently being tested in MMD patients, although inflammatory markers that have been associated with KP metabolites in the periphery and CNS will only be examined in post hoc analyses (NCT03079297). Glutamate receptor modulators  Inflammation can promote excitotoxic glutamate transmission through several mechanisms including decreased buffering by astrocytic expression of excitatory amino acid transporters (EEATs), increase release of glutamate from astrocytes and activated microglia [165, 172–174], and increased QUIN, as described above, which directly activates the n-methyl-d-aspartate (NMDA) receptor [175, 176]. Therefore, glutamate receptor antagonists may be useful in preventing excitotoxicity and oxidative stress and may reverse or prevent inflammation-related behavioral change. Indeed, in rodents, the NMDA antagonist ketamine reversed endotoxin-induced depressive-like behavior including anhedonic behavior, while having no effect on inflammation or activation of IDO in the brain [177]. Moreover, blockade of AMPA receptors was able to reverse ketamine’s effects on endotoxin-induced depressive-like behavior, indicating that the effects of ketamine were specific to its impact on glutamate signaling. Moreover, in an animal model of treatment-resistant depression, ketamine responsiveness was predicted by baseline peripheral blood levels of CRP and TNF [178]. In humans, one study in treatment-resistant depression found that patients who were most responsive to ketamine were those with the highest concentrations of serum IL-6 [43]. However, another study found that although treatment-resistant depressed patients exhibited increased IL-6 compared with controls, IL-6 and other inflammatory cytokines were not associated with response to ketamine [179]. Given the restrictions to ketamine and esketamine use (i.e., administration route, post-dose monitoring), alternative agents with equal efficacy and favorable tolerability and safety profile are being actively investigated. One example is AXS-05, a combination oral pill containing the NMDA receptor antagonist/sigma-1 receptor agonist dextromethorphan given with bupropion (to boost dextromethorphan blood levels through CYP2D6 inhibition). As phase 2 results appeared promising, with significant improvements in response and remission at 6 weeks compared with bupropion alone [180], this therapy might be particularly well-suited for treatment of depressed patients with high inflammation.

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Glutamate stabilizers  As downstream effects of inflammation both stimulate glutamate receptors and disrupt balance of intracellular and extracellular glutamate, strategies targeting reuptake mechanisms via EAATs may be beneficial in patients with high inflammation. Riluzole is one agent that may support glutamate by facilitating EAAT activity to protect against excitotoxicity [181] and has some evidence of benefit in MDD. One small open-label study found benefit in treatment-resistant depressed patients over the course of 6  weeks with riluzole monotherapy [182], while another small trial showed benefit of riluzole augmentation [183], thus providing support for future studies in MDD with high inflammation.

16.4.3 Therapies That Affect the Immune System Anti-inflammatory drugs  Results from many trials in psychiatry using anti-­ inflammatory therapies are mixed at best [59], and only a handful of studies have enriched for patients with evidence of increased inflammation and/or used drugs with known anti-inflammatory activity and little off-target effects [184]. Studies using cytokine antagonists that have potent anti-inflammatory effects have reported encouraging results for improved symptoms of anhedonia in depressed patients with increased inflammation [3, 65, 66]. Translation of these therapies is unfortunately limited, for example, by increased risk for infection, and blockade of potentially beneficial effects of innate immune signaling on other neurobiological pathways such a myelination [62, 63]. Fortunately, immunotherapies are evolving with even more specificity for inflammatory signaling pathways [185]. For example, XPro1595, a novel, first in class selective “dominant-negative” mutant variant of the human TNF protein [186], rapidly binds to and inhibits “inflammatory” signaling driven by the soluble form of TNF through soluble TNF receptors, while having no effect on the immunologic and neuro“protective” signaling driven by the transmembrane form of TNF [186– 188]. XPro1595 has demonstrated preclinical efficacy in multiple laboratory animal models of depression [189–191], including a treatment-resistance model where XPro1595 neutralized TNF of the rat and decreased peripheral blood CRP concentrations [192]. Of note, laboratory animal studies have exemplified that crossing the BBB is not required for the antidepressant effects of traditional cytokine antagonists [193], which are relatively large molecules, as reducing peripheral inflammation in MDD is the primary target [3]. However, the novel TNF antagonist XPro1595 has significant brain penetrance [194], suggesting potential human benefit for diseases like depression above and beyond the reduced risk of infection or demyelination as compared with traditional anticytokine therapies. Drugs targeting inflammatory signaling pathways, such as baricitinib, an oral Janus Kinase (JAK 1/2) inhibitor FDA-approved for the treatment of rheumatoid

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arthritis with recent additional FDA-approval for emergency use authorization for the treatment of patients hospitalized with COVID-19, are being studied [195–199]. Baricitinib significantly reduces plasma IL-6, TNF, and CRP within days after administration in humans across disease states [196–202] and might exert benefit in MDD with high inflammation. Other similar drugs in development include those that inhibit other intracellular immune pathways, toll-like receptor signaling, cell adhesion molecules, or chemokine receptors. Additionally, inhibitors of inflammasome activation via the purinergic P2X7 receptor are also being explored, including current testing in depressed patients with incomplete response to monoaminergic antidepressants and CRP ≥1 mg/L (NCT04116606). Despite considerable interest in the role of the immune system in MDD and other psychiatric disorders and its therapeutic implications, little information exists regarding the specific immunologic mechanisms required to design therapies engaging specific immune cell types. While a monocyte phenotype has traditionally been thought to represent high inflammation in MDD, a recent study clustering patients into inflammatory subgroups suggested distinct populations of high inflammation patients represented either by myeloid cells in one case or lymphoid populations in the other [203]. Accordingly, vast array of other anti-cytokine therapies that selectively target T cell cytokines include anti-IL-17 and anti-IL-12/23, which are FDA-­ approved; maraviroc which inhibits CCR5 for prevention of HIV; and plerixafor, a CXCR4 antagonist that mobilizes stem cells [204]. Immunometabolic modulation  Evidence of the metabolic and energetic reprograming used by immune cells to sustain inflammatory activation has been observed in medically stable MDD patients who had both high CRP and significant anhedonia [205]. Furthermore, immunometabolic pathways in specific cell types are being targeted for new therapies in autoimmune and inflammatory disorders [206] and align with recent data that rapamycin, an inhibitor of mTORC1 signaling involved in such processes, prolonged the antidepressant benefit of ketamine therapy [207]. Additionally, first-line treatment with dimethyl fumarate (DMF) in patients with multiple sclerosis has recently been shown to inhibit Warburg-like metabolism in immune cells via inhibiting the glyceraldehyde 3-phosphate dehydrogenase, a key enzyme of the glycolytic pathway [208]. Consistent with the role of aerobic glycolysis in activation of specific immune cell subsets, DMF inhibited inflammatory cytokines and lactate production from activated macrophages, Th1 and Th17 cells, while sparing the function of resting macrophages and regulatory T cells. Additionally, N-acetyl cysteine (NAC), a precursor to the antioxidant glutathione that reduces oxidative stress/reactive oxygen species bioproducts of intracellular immunometabolic shifts and inflammation, may both improve mitochondrial function and reduce inflammation [209–211]. NAC may also exert antidepressant activity via effects on glutamate signaling through AMPA receptors and the astroglial glutamate exchanger xCT [212, 213]. Given evidence of antidepressant efficacy of NAC, there are ongoing

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clinical trials including one with inclusion criterion of a CRP >0.85  mg/L (NCT02972398). Alternative therapies: lifestyle factors, stress reduction, neuroimmunomodulation, and microbiome  The efficacy of modifying environmental exposures and lifestyle factors that contribute to inflammation in depression have also been investigated including exercise, weight reduction, yoga, massage, tai chi, and cognitive behavioral therapy and meditation. Many of these interventions have been shown to induce a variety of immune changes including reduced inflammation [214]. For example, mindfulness meditation over 4  months increased FC between the posterior cingulate cortex and the left dorsolateral PFC, which in turn was associated with decreases in IL-6 [215]. In addition, both cognitive behavioral therapy and tai chi were associated with reduced CRP, monocyte production of inflammatory cytokines, and inflammatory gene expression in elderly patients with insomnia [216]. Both diet and exercise programs have been shown to have antidepressant and anti-­anxiety effects [217, 218] and to reduce a variety of inflammatory markers in longitudinal studies [219, 220]. A 3-month hatha yoga program also reduced endotoxin-induced peripheral blood mononuclear cell production of TNF, IL-6, and IL-1beta as well as fatigue in breast cancer survivors [221]. These studies have, however, failed to determine whether changes in inflammation or immune function are required for the efficacy of these interventions [63], or if they are generalizable to MDD patients with high inflammation and anhedonia. An elegant body of work has described a direct mechanism for neural regulation of the immune response mechanisms by stimulation of efferent vagal fibers to provide acetylcholine-mediated inhibition of the release of TNF and other cytokines from immune cells such as macrophages [222]. This anti-inflammatory cholinergic reflex can be activated by electrically stimulating the vagus and is now being capitalized on via a novel bioelectric platform that recently received designation as an FDA breakthrough device for the treatment of rheumatoid arthritis in patients intolerant of or exhibiting incomplete response to biologic drugs [223]. There is also growing interest in the role of the microbiome in a variety of neuropsychiatric disorders including MDD and its potential as a therapeutic target [224]. While the precise mechanisms by which the microbiome influences behavior are unknown, evidence suggests effects on inflammation as a plausible pathophysiologic pathway [225, 226]. These relationships have been illuminated by translational work showing induction of depressive-like behavior in mice after fecal microbiota transplant (FMT) from donors with major depression [227] and improvements in depressive and anxiety symptoms after FMT in patients with inflammatory or functional bowel disease [228, 229]. Trials examining probiotic supplementation show small but significant improvement of depressive and anxiety symptoms [230] and research on more directed therapies like FMT is warranted.

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16.5 Summary and Translational Conclusions In this chapter, extensive clinical and translational evidence is presented supporting increased inflammation and its effects on the brain as one pathophysiologic pathway to symptoms of anhedonia, reduced motivation and motor slowing as well as anxiety in MDD and other psychiatric disorders. Decreased dopamine availability and excessive glutamate may serve as mechanisms of inflammation’s impact on the brain and potential therapeutic targets for symptom reduction in psychiatric patients with elevated biomarkers of inflammation using existing or novel antidepressant strategies. Moreover, studies employing anti-cytokine therapies in depression have consistently found anhedonia to be the symptom most improved, with some support for motor retardation and anxiety. While translation potential of previously tested anti-inflammatory agents may be limited, there are a myriad of new immune-­ targeted therapies with promise for therapeutic benefit in depression including redesigned, next-generation cytokine antagonists with improved specificity for inflammatory signaling, intracellular signal transduction inhibitors FDA approved for inflammatory illness, and alternative therapies that modulate immune function via manipulation of the vagal nerve or microbiome to name a few. Despite consistent causal findings of associations between inflammation and alterations in neurotransmitters and neurocircuits relevant to MDD and other psychiatric illnesses, several challenges and considerations for translation of these concepts exist. Crucial in this regard is the need for informed trial design. For one, given strong evidence of relationships between inflammation and treatment resistance, inflammatory markers should be considered in studies examining predictors of response or selection of patients for existing antidepressant therapies in a prospective rather than post hoc fashion. For treatment development, biomarker-driven approaches should target specific therapies to patients with evidence of high inflammation (i.e., using CRP) and/or relevant symptoms like anhedonia, motor slowing, and/or anxiety and assess not only response and remission but also target engagement of relevant circuits and symptoms. Given that FC in reward and motor circuits has been identified to mediate relationships between endogenous inflammatory markers like CRP and anhedonia and psychomotor speed, functional neuroimaging biomarkers that associate with symptoms of anhedonia, motor slowing, or anxiety can serve as relevant brain biomarkers. Finally, while substantial work has established such relationships in depression, future work is needed to better understand the role of inflammation in the brain and specific behaviors and how it relates to treatment response in other disorders like schizophrenia. Another challenge for translation is that the FDA and other regulatory bodies do not currently recognize individual symptom domains as appropriate criteria for drug development, despite recent appreciation in the field of symptoms subdomains that cut across disorders and have a similar, well-defined pathophysiological basis [231]. Future efforts will clearly require advocacy in this area, particularly as it relates to treatment resistance and residual symptoms, and considering that the FDA has recognized drugs for cancer based on surrogate markers of specific genes and proteins

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involved in the growth and survival of cancer cells irrespective of clinical outcome [232]. A similar agnostic approach to treatment based on an emerging understanding of biomarkers such as genes, proteins, neurotransmitters, and circuits that underlie the biological bases of behaviors may be needed to facilitate development and approval of new drugs for treatment of psychiatric disorders. In sum, an emerging understanding of the mechanisms by which peripheral inflammation can affect neurotransmitters and relevant circuits to impact behavior and contribute to symptoms of MDD and other psychiatric disorders has provided a framework for development of novel therapies. Further identification of a platform of neuroimaging, behavioral, and peripheral biomarkers that can be used to test these therapies lends potential for future personalization of treatments targeted to biologically based subgroups of patients with transdiagnostic presentation of symptoms like anhedonia, motor slowing, and anxiety. Financial Disclosure  Dr. Felger previously consulted for Otsuka on a topic unrelated to this work.

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Chapter 17

Experimental Medicine Approaches in Early-Phase CNS Drug Development Brett A. English and Larry Ereshefsky

Abstract  Traditionally, Phase 1 clinical trials were largely conducted in healthy normal volunteers and focused on collection of safety, tolerability, and pharmacokinetic data. However, in the CNS therapeutic area, with more drugs failing in later phase development, Phase 1 trials have undergone an evolution that includes incorporation of novel approaches involving novel study designs, inclusion of biomarkers, and early inclusion of patients to improve the pharmacologic understanding of novel CNS-active compounds early in clinical development with the hope of improving success in later phase pivotal trials. In this chapter, the authors will discuss the changing landscape of Phase 1 clinical trials in CNS, including novel trial methodology, inclusion of pharmacodynamic biomarkers, and experimental medicine approaches to inform early decision-making in clinical development. Keywords  Biomarkers · Experimental medicine · Functional magnetic resonance imaging · Electrophysiology · Early phase

17.1 The Evolving Landscape in Early-Phase Clinical Trials in CNS Drug development for CNS indications continues to represent a significant unmet medical need, with psychiatric and addictive disorders representing 7% of all global burden of disease [1, 2]. In fact, the development of pharmacotherapeutics for CNS diseases has lagged other therapeutic areas with CNS drugs taking up to 20 months longer than drugs in other therapeutic areas to get toward commercial launch, with as many as 50% failing in clinical development prior to Phase 3 [3, 4]. In fact, a subsequent study by the Tufts Center for Drug Development found that success B. A. English (*) Clinical Sciences at CenExel, Brentwood, TN, USA L. Ereshefsky Clinical Sciences at CenExel, Marina Del Rey, CA, USA © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 M. Macaluso et al. (eds.), Drug Development in Psychiatry, Advances in Neurobiology 30, https://doi.org/10.1007/978-3-031-21054-9_17

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rates for CNS drugs to achieve final market approval by a regulatory agency was less than half of the approval rates for non-CNS drugs for the period 1995–2007 [3]. This has led to several of the large pharmaceutical companies to either reduce or eliminate discovery and development efforts in the CNS therapeutic area [5, 6]. The challenges to the success rates of CNS drug development are likely multifactorial to include) (1) the poor predictive validity of nonclinical rodent and primate models, (2) poor understanding of the neurobiological substrates underlying psychiatric disorders, (3) heterogeneity in the psychiatric patient population, (4) high placebo response rates, and (5) gaps in the methodologies that permit characterization of pharmacodynamic (PD) effects and their prediction of clinical end points [1, 5, 7]. These challenges have led some pharmaceutical companies to reevaluate their CNS pipeline and to retrospectively review the type and extent of data necessary to improve success through Phase 2 [6]. For example, Pfizer conducted a retrospective review of compounds in early development and found that their Phase 2 success rate was 50% less than the median success rates of other companies [8, 9]. Key findings from their review of 44 programs at Pfizer were that the majority of failures were due to lack of efficacy; however, in 43% of cases, it was not possible to conclude that the lack of clinical success was directly related to the pharmacology [8]. In fact, for those programs that achieved clinical success in Phase 2, those programs had extensive data related to (1) exposure at site of action, (2) target engagement, and (3) expression of functional pharmacologic activity, later termed the “3-pillars of survival” [8]. By focusing on programs that achieved data associated with the “3-pillars” during early development, Pfizer went from 2% success in 2010, to an impressive 21% by 2020 [9, 10]. A similar approach was taken by AstraZeneca after watching their R&D productivity drop below industry averages [11]. The results of their comprehensive review similarly not only identified obtaining data regarding the “right” exposure at the site of action and “right” target engagement improved success in Phase 3 but also identified other successful key determinants, which included selection of the “right” patient, the “right safety profile, and the “right” commercial potential in early development contributed to success [11]. These key technical determinants of success leading to improved Phase 3 completion were labeled the “five-dimensional framework” (5R framework) [11]. Adoption of the 5R-framework model, where obtaining key data related to pharmacology early in development, similarly resulted in improved candidate molecule selection and Phase 3 success, improving from 4% in 2005–10 to 19% in 2012–19 [12].

17.1.1 Challenges with Traditional Approach to Phase 1 Trials After completion of the initial nonclinical studies and submission of the data to regulatory authorities, the initiation of the Phase 1 (Ph1) clinical study represents an important milestone in the development of a new chemical entity (NCE). Phase 1

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clinical studies, also known as “first-in-human” (FiH) studies, have traditionally consisted of single ascending dose (SAD) and multiple ascending dose (MAD) studies, conducted primarily in healthy normal volunteers (HNVs) [13]. The primary objective of the Ph1 SAD/MAD study has primarily focused on characterization of the safety and tolerability profile of the NCE through collection of adverse events, clinical laboratory and vital signs. Secondary objectives of Ph1 studies include characterization of the plasma and urine pharmacokinetic (PK) parameters (e.g., absorption, distribution, metabolism, and excretion; ADME) [14, 15]. The Ph1 SAD and MAD studies consist of small cohorts (e.g. n = 8; 6 active: 2 placebo) of HNV subjects that are dosed in a sequential manner, followed by a review of the safety data and subsequent escalation of dose in a new cohort of subjects. Typically, the goal of the Ph1 SAD and MAD study has been to dose escalate up to the maximum tolerated dose (MTD), generally defined as the highest dose that achieves the intended pharmacologic effect without unacceptable adverse events (AEs), although the need to dose the NCE up to MTD in Ph1 studies conducted in healthy populations has been questioned [16–19]. The classical view of Ph1 studies was that of an initial hurdle in the sequential clinical development process prior to getting the drug into the patient population, where the latter would focus on early clinical endpoints in Ph2 proof-of-concept (PoC) studies [20]. These traditional Ph1 studies focus on the characterization of MTD for identifying the Ph2 recommended dose (P2RD), often only in HNVs, of which the MTD dose may not be the optimal dose, particularly in the target patient population [21, 22]. For drugs that are being developed for CNS indications, there is disagreement in the field on the need to determine MTD in Ph1 studies, with some points of view proposing that exploring the MTD permits a wider range of doses to be explored in subsequent development [4, 23, 24]. Lastly, some regulatory agencies such as the European Medicines Agency (EMA) have issued recent guidance regarding FiH studies that have questioned the ethics of pushing doses up to MTD in HNVs [25]. Outside collection of safety, tolerability, PK data, and a handful of rating scales, few early Ph1 study protocols included biomarker (BM) end points that may further characterize the understanding of the pharmacology of the novel drug in terms of target engagement and expression of pharmacology, or adverse event profile [26]. This was largely due to the lack of selective, reliable, or predictive BMs that could be utilized during Ph1 development to inform Ph2 PoC study considerations such as dose, patient subpopulation, etc. Thus, the traditional approach to early-phase development while obtaining initial safety and PK data left many unanswered questions regarding a novel drug’s pharmacology, which can lead to costly failures in subsequent Ph2 studies. However, advances in various fluid biomarker platforms (e.g. genomics, proteomics, and metabolomics), electrophysiology, and imaging involving academia, pharmaceutical industry, and various public-private initiatives have expanded the list of BM options that can be explored during Ph1 studies and potentially serve to validate those from the nonclinical data [27–30]. The following sections outline evolving trends that include novel study designs, inclusion of patient population in Ph1 trials, and inclusion of BMs during the SAD and MAD study.

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17.1.2 Evolution of Phase 1 Study Designs and Concepts As previously mentioned, Phase 1 study designs generally are simple, single, or multiple, sequential-dose designs where subsequent escalations to higher doses are achieved based upon the planned dose escalation scheme after review of safety data [31–33]. However, other Ph1 study designs have included grouped cross-over dose escalation, alternating cross-over, algorithm-based “3 + 3” design, and the model-­ based continuous reassessment method (CRM), with the latter using a Bayesian statistical approach to model dose escalations [14, 34, 35]. While most of the novelty in study design methodology in Ph1 studies has been applied to oncology, the statistical methods and recommendations for implementation in early-phase protocols have been published [36, 37]. The US Food and Drug Administration (FDA) and the European Medicines Agency have issued regulatory guidance on the use of adaptive design methods in clinical trials. Unlike traditional parallel-dose studies where studies are conducted to completion, adaptive design studies allow numerous approaches to be modified during study conduct that may include (a) changes in the subject allocation ratio (e.g., active vs placebo), (b) total sample size, (c) modification of eligibility criteria that can be either clinical entry criteria or BM criteria, and (d) treatment arms (e.g., dose groups) that may be dropped or added [38]. While more commonly seen in oncology early-phase studies, some Ph1 studies in CNS have incorporated “adaptive” design considerations for dose escalations based upon collection of ongoing BM data  and/or safety data. In the Ph1 single ascending dose study of risdiplam (RG7616), an orally administered survival of motor neuron 2 (SMN2) mRNA slice modifier under development for the treatment of spinal muscular atrophy (SMA), a Bayesian adaptive design approach was taken to guide dose escalations based upon risdiplam’s effect on SMN2 mRNA levels [39]. Similarly, RG7342, a metabotropic glutamate receptor 5 (mGlu5) PAM for the treatment of schizophrenia, a modified CRM using Bayesian approach was taken to avoid exposing subjects to doses above the MTD and guide subsequent dose escalations [40]. In addition to adaptive study designs, some Ph1 programs have included a novel Ph1 type translational (TxM) or experimental (ExM) medicine  study concept referred to as “proof-of-mechanism” (PoM) study that is conducted outside of the initial Ph1 SAD/MAD.  These Ph1 TxM/ExM PoM  studies can be conducted in HNVs, HNVs that are "enriched" for a specific trait (ie. trait anxiety), or in the target patient population.  Ph1 PoM studies are primarily focused on characterizing the pharmacodynamic effects of a novel drug using a particular biomarker that has proximal (or distal) effects related to the pharmacology of the study drug, or in a particular “model” of the targeted disease. Unlike Ph1 SAD/MAD studies where the BM or disease-like model is an exploratory objective, in PoM studies, the effect of the novel drug on a particular biomarker or model is the primary objective and serves to compliment the Ph1 SAD/MAD data and address key questions related to target pharmacology and “de-risk” go/no-go decisions supporting P2RD in Ph2. While most of the Ph1 PoM studies have evaluated the PD effects on a specific

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biomarker that is related to the pharmacology of the study drug, some have evaluated the effect of the study drug on a disease-like model such as scopolamine or ketamine-­reversal of cognitive deficits [41–44]. One example of a Ph1 PoM study using electrophysiology as a biomarker was the α7 nicotinic acetylcholine receptor (nAChR) partial agonist, EVP-6124 being developed for cognitive impairment associated with schizophrenia (CIAS). This was a single-center, randomized, parallel-group, double-blind, placebo-controlled study in medically stable patients with schizophrenia. Study assessments included traditional cognitive tests and event-related potential (ERP) measures, specifically mismatch negativity (MMN) and P300, both shown to be disrupted in patients with schizophrenia and correlated with cognitive deficits [45–47]. In addition, the selection of the ERP end points was based upon the pharmacologic principle that reduction of the α7 nAChR was linked to sensory deficits, including P50 [48]. Data demonstrated that both high and low doses of EVP-6124 produced statistically significant improvements in MMN and P300 relative to placebo [49]. The positive data from this trial was used to support a “go” decision for the initiation of a larger Ph2 study in CIAS [50].

17.1.3 Early Inclusion of Patients into the Phase 1 Study Increasingly, more Ph1 studies are also including small cohorts of patient populations with the targeted indication [17]. These “bridging studies,” also referred to as Ph1b studies, can be included as part of the initial Ph1 SAD/MAD, or as a separate study [27]. Particularly for NCEs being developed for psychiatric or neurologic indications, inclusion of a few cohorts of patients is encouraged, as differences in adverse events and tolerability may impact subsequent development of the NCE, by inadvertently selecting doses too low (or too high) for the target population in later trials or early termination of the development program should the AE profile be unacceptable at a specific dose be below that which is anticipated to produce clinical benefit [17, 51, 52]. The scientific rationale for these disease-dependent differences in tolerability are largely unknown; however, differences in the underlying neurobiology of the disease state and exposure to prior medications have been proposed [53]. Lastly, by characterizing the MTD in the intended population during early development, additional PK/PD modeling can be performed to potentially improve dose selections for the Ph2 proof-of-concept (POC) efficacy studies. Depending on the objectives and timelines of the clinical development plan (CDP) for the specific NCE, the inclusion of patients into the Ph1 studies can either be part of the initial SAD/MAD study or conducted under a separate protocol in a manner that is generally parallel to the MAD in HNVs. For example, in the development of Astella’s ASP4345, a selective dopamine receptor-1 (D1) positive allosteric modulator (PAM), two separate Ph1 studies were run in HNVs and patients with schizophrenia, respectively [54]. These studies consisted of a single ascending dose study in HNVs, while the multiple ascending dose study was conducted in patients diagnosed with schizophrenia or schizoaffective disorder [54]. A similar approach

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was taken during the development of Pfizer’s PF-06412562, a selective D1 and D5 partial agonist. In these studies, two separate BM-focused trials were conducted in HNVs enriched for low working memory deficits and in patients with schizophrenia, of which both studies included an extensive battery of neurocognitive testing; the use of EEG/ERPs and fMRI paradigms focused on reward and working memory [55]. Conversely, in the development of the selective phosphodiesterase 10A (PDE10A) inhibitor, TAK-063, a multiple-dose study included both healthy young Japanese subjects and in subjects with schizophrenia within a single protocol [56]. One downside to the inclusion of patients into the Ph1 study is that depending on the inclusion and exclusion criteria, patient populations generally enroll at a slower rate compared with HNVs. As an alternative to the inclusion of patients with the targeted disease into the Ph1 study, some studies have included subgroup of HNVs that serve as a “surrogate” population because they exhibit a characteristic feature of the main disease, but do not have a diagnosed condition [57]. The central tenant of this concept is that psychopathology represents an extreme variation or disruption of normal cognition and behavioral processes. This concept was highlighted by the US National Institute of Mental Health (NIMH) in 2009, upon the rollout of the Research Domain Criteria (RDoC) project (described in detail below), where mental disorders were studied transdiagnostically by breaking down these extremes in cognition and behavior into various domains and constructs that would be evaluated at the circuitry level [58, 59]. This RDoC-inspired approach was first attempted in the Ph1b experimental medicine study of PF-0641256, a D1/D5 partial agonist under development for the treatment of CIAS [55]. Previous studies had demonstrated that working memory and motivational (reward) deficits involved dopaminergic circuits that contained the D1 receptor [60]; thus, a multimodal approach focused on working memory and reward paradigms that included numerous cognitive assessments, ERP (e.g., contralateral delay activity task), and functional magnetic resonance imaging (fMRI) (e.g., N-back task) in HNVs [55]. The HNV population in this study was unique as study participants had to demonstrate low working memory capacity as determined by performance on the operational span task (O-span). The rationale for this subtype-­ specific HNV population was that (1) many cognition studies using HNVs fail to demonstrate pharmacologic enhancement and (2) low working memory deficits have demonstrated change with pharmacologic challenge [61–63]. While PF-06412562 did not improve cognitive function across the battery of tasks, further research is needed to define the proper “surrogate” population that may inform go/ no-go decisions in later patient intervention trials.

17.1.4 Incorporating Biomarkers into the Phase 1 Clinical Development Plan As an attempt to increase the pharmacologic knowledge of novel drugs during Ph1 (or Ph1b) development to improve success in later phase clinical development, many pharmaceutical companies are incorporating a myriad of biomarkers into

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these early clinical  studies. The National Institutes of Health (NIH), Biomarkers Definitions Working Group, in 1998, defined a biomarker as “a characteristic that is objectively measured and evaluated as an indicator of normal biological process, pathogenic process, or pharmacologic response to a therapeutic intervention” [64]. The NIH working group further outlined how BMs could be utilized as (1) a diagnostic tool, (2) staging of disease, (3) indicator of disease prognosis, and (4) prediction or monitoring of clinical response to an intervention [64]. Table 17.1 describes biomarker nomenclature and some of the methods used. Additionally, the NIH Biomarker and Surrogate Endpoint Working Group has identified three classes of biomarkers: Type 0, biomarkers that track the natural course of the disease; Type 1, biomarkers that examine the effects of an intervention of a known mechanism without strict relationship to clinical outcome; and Type 2, biomarkers considered “surrogate end points” and optimally predictive of clinical outcome [74]. The decision to include BMs into the Ph1 studies should be considered as early in the development program of an NCE as possible to ensure proper integration of the BM plan into the CDP, as the selection of a specific BM may inform crucial questions that impact study designs and the role that the BM will play within the Ph1 development plan. During the development of the early CDP, key questions that a BM strategy is intended to address should be outlined as to support go/ no-go decision  criteria for Ph2 and then operationalized within the Ph1 study protocols. Key questions include, but are not limited to, (1) what role will the biomarker serve within the Ph1 studies (e.g., exploratory or confirmatory), (2) type of biomarker (e.g., pharmacodynamic and safety), (3) translatability of the biomarker from the nonclinical to clinical, (4) the use of multimodal biomarkers in the Ph1 study (e.g., plasma-based and electrophysiology), and (5) feasibility of incorporating into the Ph1 study (e.g., operational logistics and subject burden) [27, 75, 76]. Additionally, if the BM is a pharmacodynamic BM, additional considerations may be included if the measure(s) will demonstrate proof-­ of-­ pharmacology, proof-of-mechanism, correlation with a clinical endpoint, etc. [27, 77]. Lastly, based upon the objectives of the Ph1 development plan, the BM strategy may either be included in the initial Ph1 SAD or MAD study, or conducted separately, in an experimental medicine study that can run in a nested fashion, concurrent with the Ph1 SAD/MAD (Fig. 17.1).

17.2 Leveraging Experimental Medicine to Support Early Decision-Making in Early-Phase Trials As previously mentioned, despite advances in basic and systems neuroscience, including advances in technologies to better understand psychiatric and neurologic disorders, the discovery of novel drugs and their successful clinical development has been challenging. To address these challenges, a new model of early-phase clinical development was introduced: the experimental medicine study that aimed to merge known mechanism-of-action of the NCE and knowledge of the neurobiology

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Table 17.1  Biomarker nomenclature [24, 27, 65–73] Biomarker class Use type Susceptibility Risk

Mechanistic

Prognostic

Diagnostic

Monitoring

Intervention

Predictive

Enriched

Definition Biomarker that indicates the likelihood of developing a disease Biomarker that identifies the likelihood of a clinical event and disease recurrence or progression; can be used to stratify patients in clinical trials Biomarker used to confirm diagnosis of disease Biomarker measured longitudinally to assess the status of disease after an intervention Biomarker that predicts that a particular patient will respond to the intervention Selection of a specific population predicted to exhibit a response to an intervention

Pharmacodynamic Biomarker that demonstrates a direct or indirect effect on a biological response to an intervention

Safety

Surrogate endpoint

Biomarker before or after an intervention indicative of toxicity such as an adverse event (e.g., ARIA) Biomarker that serves an indirect measure and predictive of benefit on a clinical end point

Biomarker methods Blood/plasma/CSF (e.g., APOE ε4), qEEG, ERP, PSG, sMRI, rsMRI, fMRI, PET Blood/plasma/CSF (e.g., β-amyloid), qEEG, ERP, PSG, sMRI, rsMRI, fMRI, PET

Blood/plasma/CSF (e.g., β-amyloid), qEEG, sMRI, PET Blood/plasma/CSF (e.g., β-amyloid), sMRI, PET Blood/plasma/CSF, qEEG, ERP, fMRI, rsMRI Blood/plasma/CSF (e.g., β-amyloid), qEEG, ERP, PSG, sMRI, rsMRI (e.g., functional connectivity), fMRI (e.g., task based), PET Blood/plasma/CSF (e.g., β-amyloid), qEEG, ERP, PSG, sMRI, rsMRI (e.g., functional connectivity), fMRI (e.g., task based), PET Blood/plasma/CSF (e.g., GFAP), sMRI (e.g., ARIA)

Blood/plasma/CSF (e.g., β-amyloid reduction)

Def: APOE4 apolipoprotein-4, ARIA amyloid related imaging abnormality, CSF cerebrospinal fluid, ERP evoked related potential, fMRI functional magnetic resonance imaging, GFAP glial fast acidic protein, PET positron emission tomography, PSG polysomnography, qEEG quantitative electroencephalography, rsMRI resting state magnetic resonance imaging, sMRI structural magnetic resonance imaging

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A. BM Plan incorporated into SAD/MAD Cohort 5 (Dose E) Cohort 4 (Dose D) Cohort 3 (Dose C) Cohort 2 (Dose B)

SAD

Cohort 1 (Dose A)

BM Cohort 3 (Dose D) BM Cohort 2 (Dose C)

BM Cohort 1 (Dose B) Cohort 4 (Dose D) Cohort 3 (Dose C) Cohort 2 (Dose B)

MAD

BM Cohort 2 (Dose C) BM Cohort 1 (Dose B)

Cohort 1 (Dose A)

B. BM plan separate from the Ph1 SAD/MAD Ph1 SAD/MAD

Cohort 3 (Dose C) Cohort 2 (Dose B)

SAD

Cohort 1 (Dose A)

MAD

Cohort 3 (Dose C) Cohort 2 (Dose B)

Cohort 1 (Dose A)

Ph1b BM study

BM Cohort 1 (SD or MD Dose B) BM Cohort 1 (SD or MD Dose C)

Fig. 17.1  An illustrative approach to the incorporation of a biomarker strategy into either Ph1 SAD/MAD studies (a) or as a separate experimental medicine (EM) study (b). In the SAD and MAD studies, multimodal biomarkers can be applied without running separate cohorts; however, the investigator is cautioned to overburden subjects in the Ph1 SAD/MAD where the primary objective if safety tolerability. In (a), the Ph1 SAD/MAD biomarker cohort could initiate upon safety/tolerability clearance of the previous dose level and run in parallel with safety cohorts. In (b), the biomarker cohorts are conducted outside the Ph1 SAD/MAD program, while doses selected for these cohorts are based upon safety/tolerability from Ph1 SAD MAD. Def: BM biomarker, EM experimental medicine, MAD multiple ascending dose, SAD single ascending dose. (Adapted from: English et al. [27])

of the targeted disease state. To support this approach, two major initiatives were introduced by the NIH.  The first initiative was the National Institute of Mental Health (NIMH) Research Domain Criteria (RDoC) launched in 2009, which was a novel approach to address shortfalls in the diagnostic nosology of psychiatric disorders and to leverage decades of research into the neurobiological circuits and their dysfunction in psychiatric disorders [58, 59, 78]. The second initiative launched in 2012 was the NIMH “Fast-Fail initiative,” aimed at characterizing the pharmacodynamic effects of novel NCEs during early clinical development by incorporating pharmacodynamic biomarkers that could serve as intermediate end points to

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neurocircuitry underlying specific behavioral or cognitive domains [79–81]. Additionally, other partnerships between the pharmaceutical industry, academia, and private foundations such as the Foundation for NIH’s Biomarkers Consortium Neuroscience Steering Committee, the Human Connectome Project, the Psychiatric Genomics Consortium, the ENIGMA-EEG Working Group, the NIMH-Industry New Therapeutics Use Program, and the Innovative Medicines Initiative New Meds Consortium have served to bring key stakeholders together to address challenges in CNS drug development [82–85]. The NIMH RDoC and Fast-Fail approaches and their implementation in early clinical development are described below.

17.2.1 NIMH Research Domain Criteria (RDoC) Framework and the “Fast-Fail” Initiative As part of the NIMH’s Strategic Plan, the RDoC initiative was to link advances in neurobiology with the traditional approach of classifying psychiatric disorders based upon clinical nosology [86]. Conceptually, RDoC “deconstructed” human behavior and cognition into six neuropsychological “domains” of human functioning, followed by “constructs” or processes underlying these domains, and finally, “units of analysis” that included specific genetic, neurocircuit, behavioral measures, and selfreport assessments [78, 86] The five initial RDoC domains included the following: (1) positive valence systems (e.g., reward), (2) negative valence systems (e.g., fear/ threat), (3) cognitive systems (e.g., working memory), (4) social processes (e.g., communication), and (5) arousal/regulatory systems (e.g., sleep circadian) [86, 87]. A sixth domain, sensorimotor systems was added in 2019 [88]. By “deconstructing” complex psychiatric syndromes into various domains, constructs, and units, researchers could investigate these behaviors transdiagnostically to identify underlying molecular or neural mechanisms that were dysfunctional. While a significant amount of research has been published across psychiatric and neurodevelopmental disorders, some have criticized the limitations of RDoCs and its ability to characterize complex psychiatric disorders vs extremes of normal human behavior [89, 90]. The NIMH “Fast-Fail” Program, initially termed by Paul et al., was an initiative aimed at incorporating novel proof-of-mechanism (PoM)-specific biomarkers in an early phase (Ph1b or Ph2a), experimental medicine focused study with the key objective of characterizing the effects of a novel compound on a PoM-specific BM in order to confirm pharmacology and target engagement and increase confidence in go/no-go decisions [81, 91]. The Fast-Fail PoM approach was to sequentially collect data related to target engagement (e.g., positron emission tomography; PET), followed by effect of the molecule on an established biomarker that measured the underlying neurocircuitry associated with a clinical construct (e.g., anhedonia). Thus, molecules that demonstrated sufficient target occupancy, followed by modulating the neurocircuitry associated with a clinically measurable end point, would then be advanced forward into later phase trials. For those molecules that failed to

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engage the target or modulate the expected biology, these molecules would be considered as having “failed” in early in clinical development an thus potentially avoid costly later-phase studies [79, 81, 91]. In 2012, the NIMH launched three funded programs under the Fast-Fail program that focused on different psychiatric populations: psychotic (FAST-PS), mood and anxiety (FAST-MAS), and autism spectrum disorder (FAST-AS) [80]. The FAST-PS study evaluated a functional MRI (fMRI)-based pharmacodynamic biomarker using ketamine as a drug-induced surrogate of psychosis that could be utilized in other trials. The FAST-AS study evaluated resting state EEG as a pharmacodynamic BM to evaluate novel therapies in AS, while the FAST-MAS evaluated a novel kappa-­ opioid receptor (KOR) antagonist on a task-based fMRI task of reward salience [80, 92].

17.2.2 Incorporating RDoC and Fast-Fail Concepts: A Proof-­of-Mechanism Study One of the first studies to implement the NIMH’s Fast-Fail approach, incorporating an RDoC-inspired biomarker endpoint, tested a repositioned KOR antagonist, JNJ-67953964, to potentially treat anhedonia in major depressive disorder (MDD) by measuring behavioral performance using the monetary incentive delayed (MID) task in the fMRI as a measure of ventral striatal activation [79]. The Fast-MAS PoM study was a multisite, Ph2a, double-blind, placebo-controlled, fixed-dose, parallel-­ group study of JNJ-67953964 vs placebo for 8 weeks in patients meeting DSM-5 mood or anxiety disorder criteria who demonstrated significant anhedonia as assessed by the Snaith Hamilton Pleasure Scale score ≥20 [79]. Anhedonia, a construct within the negative valence domain, has been demonstrated to be modulated by reward-related neurocircuitry in the ventral striatum [93]. Additionally, nonclinical data demonstrated that activation of the KOR blunted dopamine release in the striatum and induced negative mood, while inhibition of KOR increased dopamine release and blunted negative behavior [94–96]. To evaluate PoM with the KOR antagonist, the primary outcome measure was the activation of the ventral striatum during anticipation of monetary gain using the MID task in the fMRI [79]. The MID task was selected based upon previous work, including patients with MDD receiving open-label citalopram [97–99]. Results demonstrated that JNJ-67953964 significantly increased ventral striatum activation during reward anticipation on the MID task as measured by fMRI compared with placebo (baseline-adjusted mean: JNJ-67953964, (0.72 (s.d. = 0.67); placebo, 0.33 (s.d. = 0.68); F (1, 86) = 5.58, P